[ { "id": "https://openalex.org/W4410876612", "doi": "10.2139/ssrn.5276482", "title": "Energy and Carbon Analysis of Multirotor Uavs for Urban Parcel Delivery", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": "en", "authors": [ "SungHyuk Choi" ], "first_author": "SungHyuk Choi", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Multirotor", "Energy (signal processing)", "Carbon fibers", "Environmental science", "Energy analysis", "Business", "Computer science", "Aerospace engineering", "Engineering", "Physics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5276482" }, { "id": "https://openalex.org/W4414299607", "doi": "10.1016/j.cie.2025.111523", "title": "The flying sidekick traveling salesman problem with multiple drops: An effective heuristic approach", "year": 2025, "publication_date": "2025-09-17", "type": "article", "language": "en", "authors": [ "Sarah K. Schaumann", "Abhishake Kundu", "Juan C. Pina-Pardo", "Matthias Winkenbach", "Ricardo A. Gatica", "Stephan M. Wagner", "Timothy I. Matis" ], "first_author": "Sarah K. Schaumann", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Heuristic", "Truck", "Stylized fact", "Payload (computing)", "2-opt" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2025.111523" }, { "id": "https://openalex.org/W4392397471", "doi": "10.2139/ssrn.4745362", "title": "Intelligent Parcel Delivery Scheduling Using Truck-Drones to Cut Down Time and Cost", "year": 2024, "publication_date": "2024-01-01", "type": "preprint", "language": "en", "authors": [ "Tamer Ahmed Farrag", "Mai A. Farag", "Mostafa A. Elhosseini", "Aboul Ella Hassanien", "Heba Askr" ], "first_author": "Tamer Ahmed Farrag", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Scheduling (production processes)", "Computer science", "Transport engineering", "Operations research", "Real-time computing", "Engineering", "Operations management", "Automotive engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4745362" }, { "id": "https://openalex.org/W4387090438", "doi": "10.1109/sest57387.2023.10257390", "title": "Lifespan-Prolonging Dual Battery System Online Operation Scheduling for In-City Drone Delivery", "year": 2023, "publication_date": "2023-09-04", "type": "conference-paper", "language": "en", "authors": [ "Yiliang Yuan", "Jiahang Xie" ], "first_author": "Yiliang Yuan", "venue": null, "publisher": null, "abstract": "Delivery conducted by drones plays a significant role in in-city delivery and last-mile delivery, owing to their fast speed and economy. However, since drones are powered by batteries, battery lifetime and the associated replacement cost are one of the main hindrances to more cost-efficient drone applications in delivery. In this work, the lifetime-prolonging dual battery online scheduling problem for drone operation is introduced. The dual battery consists of a new battery bank and a second-life battery bank, in which the scheduling can regulate the output of the new battery pack and thus extend its lifespan and meanwhile make full use of the abundant second-life battery resources. This scheduling problem can be solved optimally offline using a dynamic programming algorithm. However, online decisions in this dual battery system need to be made without future information. Thus the battery degradation cost is amortized into the operational cost per time interval, and an online algorithm is proposed. The proof of the competitive ratio of the online algorithm compared to the offline optimal is provided.", "keywords": [ "Drone", "Battery (electricity)", "Computer science", "Scheduling (production processes)", "Dual (grammatical number)", "Real-time computing", "Job shop scheduling", "Online algorithm", "Reliability engineering", "Embedded system", "Engineering", "Operations management" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.1109/sest57387.2023.10257390" }, { "id": "https://openalex.org/W7162285099", "doi": "10.1016/j.tre.2026.104962", "title": "Designing flexible service strategies for urban drone Delivery: A hybrid Simulation-Optimization framework", "year": 2026, "publication_date": "2026-05-25", "type": "article", "language": "en", "authors": [ "Zhijie Yang", "Fei Ma", "Yu Wang", "Liu Qing", "Qipeng Sun", "Gangyan Xu", "Wei Ren" ], "first_author": "Zhijie Yang", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Service (business)", "Key (lock)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2026.104962" }, { "id": "https://openalex.org/W7162241598", "doi": "10.5281/zenodo.20215093", "title": "Estudo Sobre Alternativas para o Last Mile no Contexto do e-Commerce", "year": 2026, "publication_date": "2026-01-05", "type": "article", "language": "pt", "authors": [ "Kleber Ferreira de Souza Carvalho", "Aguinaldo Eduardo de Souza" ], "first_author": "Kleber Ferreira de Souza Carvalho", "venue": "Advances in Global Innovation & Technology", "publisher": null, "abstract": "A expansão do comércio eletrônico no Brasil tem imposto à logística urbana uma série de novos desafios, sobretudo no que se refere à fase final do processo de entrega, conhecida como última milha. Sendo assim, o objetivo geral desse estudo é analisar alternativas viáveis para a etapa da última milha no ambiente do comércio eletrônico. A metodologia adotada foi a pesquisa de natureza exploratória, com abordagem comparativa entre estudos de caso. Foram analisadas duas investigações que abordaram diferentes estratégias para otimizar as operações de distribuição final, considerando soluções baseadas em dados reais e alternativas tecnológicas inovadoras, como o uso de inteligência artificial (IA), veículos autônomos, drones e práticas sustentáveis. Os principais obstáculos identificados foram a complexidade das entregas urbanas, os altos custos operacionais, a necessidade de prazos reduzidos e as expectativas crescentes dos consumidores. Os resultados evidenciam a importância de investimentos em inovação tecnológica e de um planejamento logístico eficiente para superar os entraves da última milha, proporcionando maior eficiência, redução de custos e melhoria na experiência do consumidor. Conclui-se que a gestão eficaz da última milha se configura como um diferencial competitivo fundamental no ambiente contemporâneo do comércio eletrônico.", "keywords": [ "Context (archaeology)", "Work (physics)", "Process (computing)", "Data collection" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20215093" }, { "id": "https://openalex.org/W7111355032", "doi": "10.18267/j.aip.257.html", "title": "Optimization in Routing and Vehicle Selection for E-commerce Last Mile Logistics: Bibliometric Analysis", "year": null, "publication_date": null, "type": "article", "language": null, "authors": [ "Sari Andarwati Kunharyanto", "Ratna Mayasari", "Dili Oktaviana" ], "first_author": "Sari Andarwati Kunharyanto", "venue": "RePEc: Research Papers in Economics", "publisher": "Federal Reserve Bank of St. Louis", "abstract": "Background: The study investigates the emerging concept of Last Mile Logistics (LML), focusing on optimization routing for e-commerce deliveries. This research addresses the growing demand for efficient delivery systems driven by the rise of online shopping and technological advancements.Objective: This article aims to analyse existing literature, identify trends and highlight gaps in LML research.Methods: A systematic approach was used for the selection of studies and then bibliometric analysis was used to map and evaluate relevant studies. The Scopus citation database was used to gather peer-reviewed articles from 1999 to 2023. R-Studio and VOS Viewer were employed for data analysis and visualization. The initial search yielded 3, 898 articles, which were filtered down to 1, 606 articles. Key findings include the identification of the most productive journals, top-cited articles and influential keywords in LML research.Results: The study significantly emphasizes variables such as distance, costs, energy consumption and delivery time in logistics optimization. E-commerce emerged as a predominant topic, with substantial discussions on technology and transportation within LML. The research underscores the critical role of LML in the success of e-commerce.Conclusion: The findings highlight the need for ongoing innovation and optimization in delivery logistics to enhance efficiency and meet consumer demands. Future research should address the gaps identified, particularly in the context of emerging technologies such as autonomous vehicles and drones, to further improve last mile delivery systems.", "keywords": [ "Context (archaeology)", "Identification (biology)", "Selection (genetic algorithm)", "Last mile (transportation)", "Energy consumption", "Vehicle routing problem", "Scopus", "Routing (electronic design automation)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://aip.vse.cz/doi/10.18267/j.aip.257.html" }, { "id": "https://openalex.org/W2740819241", "doi": "10.13009/eucass2017-505", "title": "SpaceLiner Concept as Catalyst for Advanced Hypersonic Vehicles Research", "year": 2017, "publication_date": "2017-01-01", "type": "conference-paper", "language": "en", "authors": [ "Martin Sippel", "Cecilia Valluchi", "Leonid Bussler", "KRUMMEN, Sven", "Sven Stappert" ], "first_author": "Martin Sippel", "venue": "elib (German Aerospace Center)", "publisher": "Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)", "abstract": "There are renewed interest in the development of propellers due to the increased and extensive applications of unmanned air vehicles (UAVs) or commonly known as drones for aerial photography, parcel delivery, aerial surveillance, inspection, marketing and many other applications. These UAVs or drones are usually powered by fixed pitch propellers of small diameters driven by electrical motors. The required operating conditions for achieving the designed tasks in terms of lifts and speeds are typically in contrast with the need for having quieter or even silent UAVs or drones. The desire for light weight UAVs or drones has resulted in the use of carbon fibre composite propellers and such carbon fibre composite propellers have become common parts for the design and assembly of UAVs or drones. The present research would explore the use of natural fibre composites, for example, flax fibres composites and also hybrid fibre composites in mitigating the propeller noise with the increased damping characteristics due to the introduction of natural fibres. Typical natural fibre and hybrid fibre propellers for drones were fabricated for benchmarking with commercially available carbon fibre composite propellers as well as composite propellers produced by 3d printing. The noise characteristics at various rotating speeds for propellers made of both the natural fibre and hybrid composites as well as commercially available carbon composites were measured in an anechoic chamber by attaching the propellers to a motor on a stationary platform. The natural fibre and hybrid fibre composite propellers were also fixed onto standard quadrotor drones for assessing the flight performance besides the noise characteristics.", "keywords": [ "Propulsion", "Systems engineering", "Aerospace engineering", "Aeronautics", "Hypersonic speed", "Rocket (weapon)", "Key (lock)", "Division (mathematics)", "Engineering", "Spacecraft propulsion", "Space (punctuation)", "Computer science" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://elib.dlr.de/113153/1/EUCASS2017-2.pdf" }, { "id": "https://openalex.org/W4313428680", "doi": "10.1109/urtc56832.2022.10002251", "title": "Improving the Performance of Computer Vision Algorithms for the Multi-Mode Hybrid Drone Delivery System", "year": 2022, "publication_date": "2022-09-30", "type": "conference-paper", "language": "en", "authors": [ "Ronald Leung", "Chelsy Goodwill", "Alexander Dong", "Kareena Shah", "Mohammad Katibeh" ], "first_author": "Ronald Leung", "venue": null, "publisher": null, "abstract": "Drone deliveries provide an innovative alternative to current last-mile delivery solutions; however, drones are limited by their short flight time. To overcome this, researchers devised the Multi-Mode Hybrid Drone Delivery System, in which a plane transports a drone to deliver a package. The preexisting system requires improvements to its computer vision algorithms to enable the drone to redock to the plane. This research aims to evaluate and improve the performance of the object detection algorithm. Three tests are performed to establish performance metrics: the Frequency, Distance Tracking, and Horizontal Position Accuracy Tests. Results reveal that decreasing the dimensions of the camera’s input significantly increases the processing speed of the computer vision algorithm. A new method is proposed that improves the accuracy of the drone’s positional tracking, providing the precision needed to make the redocking process possible.", "keywords": [ "Drone", "Computer science", "Mode (computer interface)", "Artificial intelligence", "Algorithm", "Human–computer interaction" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.1109/urtc56832.2022.10002251" }, { "id": "https://openalex.org/W7140030091", "doi": "10.55041/ijcope.v2i3.113", "title": "AI-Driven Autonomous Drone Delivery: An Empirical Study of Consumer Awareness, Trust, and Adoption", "year": 2026, "publication_date": "2026-03-22", "type": "article", "language": null, "authors": [ "Samridhi Nagpal", "Tashi Sadh", "Mani Pushpak", "Chhavi Jain" ], "first_author": "Samridhi Nagpal", "venue": "International Journal of Creative and Open Research in Engineering and Management", "publisher": null, "abstract": "The rapid expansion of e-commerce has significantly increased the demand for faster and more efficient delivery systems. Traditional delivery methods often face challenges such as traffic congestion, high fuel costs, delays, and environmental concerns. In this context, Artificial Intelligence (AI)-enabled autonomous drones have emerged as a promising solution for last-mile delivery. This study adopts an empirical approach based on primary data collected through a structured questionnaire. It examines consumer awareness, perception, willingness to adopt, and trust in AI-based drone delivery services. The findings reveal that while awareness and perceived benefits are high, actual adoption remains limited due to concerns related to cost, safety, and trust. The study concludes that AI-driven drone delivery has strong future potential, but its success depends on improving affordability, regulatory support, and consumer confidence.", "keywords": [ "Drone", "Empirical research", "Face (sociological concept)", "Food delivery", "Empirical evidence" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ijcope.org/wp-content/uploads/2026/03/AI-Driven-Autonomous-Drone-Delivery-An-Empirical-Study-of-Consumer-Awareness-Trust-and-Adoption.pdf" }, { "id": "https://openalex.org/W7162249241", "doi": "10.5281/zenodo.20215094", "title": "Estudo Sobre Alternativas para o Last Mile no Contexto do e-Commerce", "year": 2026, "publication_date": "2026-01-05", "type": "article", "language": "pt", "authors": [ "Kleber Ferreira de Souza Carvalho", "Aguinaldo Eduardo de Souza" ], "first_author": "Kleber Ferreira de Souza Carvalho", "venue": "Advances in Global Innovation & Technology", "publisher": null, "abstract": "A expansão do comércio eletrônico no Brasil tem imposto à logística urbana uma série de novos desafios, sobretudo no que se refere à fase final do processo de entrega, conhecida como última milha. Sendo assim, o objetivo geral desse estudo é analisar alternativas viáveis para a etapa da última milha no ambiente do comércio eletrônico. A metodologia adotada foi a pesquisa de natureza exploratória, com abordagem comparativa entre estudos de caso. Foram analisadas duas investigações que abordaram diferentes estratégias para otimizar as operações de distribuição final, considerando soluções baseadas em dados reais e alternativas tecnológicas inovadoras, como o uso de inteligência artificial (IA), veículos autônomos, drones e práticas sustentáveis. Os principais obstáculos identificados foram a complexidade das entregas urbanas, os altos custos operacionais, a necessidade de prazos reduzidos e as expectativas crescentes dos consumidores. Os resultados evidenciam a importância de investimentos em inovação tecnológica e de um planejamento logístico eficiente para superar os entraves da última milha, proporcionando maior eficiência, redução de custos e melhoria na experiência do consumidor. Conclui-se que a gestão eficaz da última milha se configura como um diferencial competitivo fundamental no ambiente contemporâneo do comércio eletrônico.", "keywords": [ "Context (archaeology)", "Work (physics)", "Process (computing)", "Data collection" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20215094" }, { "id": "https://openalex.org/W4416613035", "doi": "10.48550/arxiv.2505.23584", "title": "Collaborative Last-Mile Delivery: A Multi-Platform Vehicle Routing Problem With En-route Charging", "year": 2025, "publication_date": "2025-05-29", "type": "preprint", "language": "en", "authors": [ "Sumbal Malik", "Majid Khonji", "Khaled Elbassioni", "Jorge M.M. Dias" ], "first_author": "Sumbal Malik", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "The rapid growth of e-commerce and the increasing demand for timely, cost-effective last-mile delivery have increased interest in collaborative logistics. This research introduces a novel collaborative synchronized multi-platform vehicle routing problem with drones and robots (VRP-DR), where a fleet of $\\mathcal{M}$ trucks, $\\mathcal{N}$ drones and $\\mathcal{K}$ robots, cooperatively delivers parcels. Trucks serve as mobile platforms, enabling the launching, retrieving, and en-route charging of drones and robots, thereby addressing critical limitations such as restricted payload capacities, limited range, and battery constraints. The VRP-DR incorporates five realistic features: (1) multi-visit service per trip, (2) multi-trip operations, (3) flexible docking, allowing returns to the same or different trucks (4) cyclic and acyclic operations, enabling return to the same or different nodes; and (5) en-route charging, enabling drones and robots to recharge while being transported on the truck, maximizing operational efficiency by utilizing idle transit time. The VRP-DR is formulated as a mixed-integer linear program (MILP) to minimize both operational costs and makespan. To overcome the computational challenges of solving large-scale instances, a scalable heuristic algorithm, FINDER (Flexible INtegrated Delivery with Energy Recharge), is developed, to provide efficient, near-optimal solutions. Numerical experiments across various instance sizes evaluate the performance of the MILP and heuristic approaches in terms of solution quality and computation time. The results demonstrate significant time savings of the combined delivery mode over the truck-only mode and substantial cost reductions from enabling multi-visits. The study also provides insights into the effects of en-route charging, docking flexibility, drone count, speed, and payload capacity on system performance.", "keywords": [ "Drone", "Payload (computing)", "Scalability", "Heuristic", "Truck", "Vehicle routing problem", "Routing (electronic design automation)", "Robot" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2505.23584" }, { "id": "https://openalex.org/W7161125795", "doi": "10.2139/ssrn.6732138", "title": "Assessing the Impact of Online Shopping and Drone Delivery on Socio-Economic Profiles and CO2 Emissions", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Ziyue Li", "Qianwen Guo" ], "first_author": "Ziyue Li", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Software deployment", "Popularity", "Truck", "Traffic congestion" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.6732138" }, { "id": "https://openalex.org/W7198312143", "doi": null, "title": "Implementation of artificial intelligence and robotic automation technologies in e-commerce logistics to optimize the “last mile”", "year": 2025, "publication_date": "2025-11-01", "type": "dissertation", "language": "uk", "authors": [ "Ігнатенко Анна Віталіївна", "Марина Володимирівна Котова" ], "first_author": "Ігнатенко Анна Віталіївна", "venue": "Electronic Institutional Repository of the National Aviation University of Ukraine (National Aviation University, Ukraine)", "publisher": "National University \"Kyiv Aviation Institute\"", "abstract": "1. Accenture. (2021). Future of Last-Mile Delivery: The E-commerce Logistics Race. 2. Agatz, N. A., Bouman, P., & Schmidt, M. (2018). Optimization Approaches for the Last Mile in E-commerce: Literature Review and Future Research. Transportation Science, 52(4), 1146-1166. 3. Winkelbauer, M., & Störk, J. (2021). Dynamic vehicle routing for ondemand food delivery: a deep reinforcement learning approach. European Journal of Operational Research, 290(3), 903-918. 4. Luo, S., Liu, C., & Zhang, W. (2020). Delivery robots and the last mile: Modeling the operational costs and environmental impacts. International Journal of Production Economics, 223, 107519. 5. Wang, R., & Li, S. (2022). Unmanned Aerial Vehicles (UAVs) in Last-Mile Logistics: Challenges and Opportunities. IEEE Transactions on Intelligent Transportation Systems, 23(1), 12-25. 6. Gunes, Z., & Karagül, A. (2020). The role of Autonomous Mobile Robots (AMR) in fulfillment centers: A review of key design factors and operational benefits. Procedia Computer Science, 180, 52-61. 7. Deloitte. (2019). The future of mobility: The last-mile delivery challenge. 8. European Commission. (2020). Study on Regulatory framework for the deployment of autonomous vehicles in the EU.", "keywords": [ "Software deployment", "Automation", "Robot", "Key (lock)", "Robotics", "Mobile robot" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://er.kai.edu.ua/handle/KAI/69426" }, { "id": "https://openalex.org/W7204450903", "doi": "10.1299/jamdsm.2026jamdsm0044", "title": "Mixed integer programs of routing and scheduling of minimizing a generalized makespan for a truck-drone parcel delivery system", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": "en", "authors": [ "Kim Cuc Vo Thi", "Yoshiyuki Karuno" ], "first_author": "Kim Cuc Vo Thi", "venue": "Journal of Advanced Mechanical Design Systems and Manufacturing", "publisher": "Japan Society Mechanical Engineers", "abstract": "We treat an issue of routing and scheduling for a parcel delivery system, which is composed of a single carrier truck and multiple identical drones. The carrier truck basically plays the role of a mobile depot of drones, and the drones perform the last-mile delivery of a parcel from the carrier truck at a stop to each of all the drone-served customers and of some flexible customers. The carrier truck also brings a parcel directly to such a customer that either can be or must be served by the carrier truck, i.e., it is either a flexible customer or a truck-served customer. The carrier truck delivers a parcel to a flexible customer if the direct delivery is more advantageous than the last-mile delivery by a drone. We propose a mixed integer program of this issue, which is an extended version of an existing formulation for a fixed truck route model of such a truck-drone system. The objective is to minimize the sum of the total duration over available truck stops and a weighted travel time of the carrier truck, i.e., it is to minimize a generalized makespan. We also demonstrate the solution quality of the proposed mixed integer program empirically by utilizing a mixed integer programming solver, and we observe an effect of the weight in the objective function and an effect of the existence of flexible customers in the numerical results.", "keywords": [ "Job shop scheduling", "Scheduling (production processes)", "Integer programming", "Routing (electronic design automation)", "Integer (computer science)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.jstage.jst.go.jp/article/jamdsm/20/5/20_2026jamdsm0044/_pdf" }, { "id": "https://openalex.org/W4415971155", "doi": "10.1109/tro.2025.3629808", "title": "Efficient Routing for Multitruck Multidrone Package Delivery With Precedence Constraints", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": null, "authors": [ "Xiaoshan Bai", "Baode Li", "Jianqiang Li", "Zongze Wu", "Weidong Zhang", "Shuzhi Sam Ge" ], "first_author": "Xiaoshan Bai", "venue": "IEEE Transactions on Robotics", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "As the demand for efficient parcel delivery continues to grow in the logistics industry, optimizing multi-robot task assignment has become crucial for enhancing overall delivery performance. This paper addresses the precedence-constrained multi-truck multi-drone package delivery task assignment problem, where each truck coordinates with a drone to serve multiple dispersed customers under precedence constraints that specify the required order of service. While trucks deliver packages to designated customers, drones can simultaneously serve other customers, subject to their limited flight endurance and payload capacity. To tackle this challenge, a three-phase heuristic algorithm is proposed to minimize the total delivery time required to serve the last customer while ensuring all precedence constraints are satisfied. In the first phase, an extended minimum marginal cost algorithm is applied to quickly construct truck-only routes that comply with precedence constraints. In the second phase, a splitting algorithm combined with an endurance checking procedure is employed to generate hybrid truck–drone routes considering drone limitations. In the final phase, a variable neighborhood descent approach is introduced to further improve the solution by strategically perturbing the truck-only routes. Extensive simulations and experiments demonstrate that the proposed three-phase heuristic algorithm consistently achieves higher-quality solutions with reduced computation time compared with the widely used adaptive large neighborhood search method.", "keywords": [ "Drone", "Task (project management)", "Truck", "Routing (electronic design automation)", "Payload (computing)", "Heuristic", "Variable neighborhood search", "Computation", "Vehicle routing problem" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tro.2025.3629808" }, { "id": "https://openalex.org/W4366223646", "doi": "10.30880/paat.2022.02.01.009", "title": "The Augmentation of a Flight Control Mechanism for a Hybrid Fixed-Wing VTOL Drone for Parcel Delivery", "year": 2022, "publication_date": "2022-08-28", "type": "article", "language": "en", "authors": [ "Universiti Tun Hussein Onn Malaysia", "Mohamad Nadjmi Mohd Shakir See", "Mohd Fadhli Zulkafli", "Universiti Tun Hussein Onn Malaysia", "Muhammad Fahmi Pairan", "Universiti Tun Hussein Onn Malaysia", "Seyhrvin Kumar Chakraverty", "Universiti Tun Hussein Onn Malaysia", "Izzat Khair Mahmud", "Universiti Tun Hussein Onn Malaysia" ], "first_author": "Universiti Tun Hussein Onn Malaysia", "venue": "Progress in Aerospace and Aviation Technology", "publisher": "Penerbit UTHM", "abstract": "Several companies are experimenting with multicopters drones to deliver packages to customers. Although they are less aerodynamically efficient than fixed-wing aircraft, their ability to do the vertical take-off and landing (VTOL) makes them ideal for delivery services. In this study, two methodologies will be used to build the drone which is software simulation and experimental approach. Software such as SIMNET is used to simulate and design an electronic operation of the drone while Mission Planner is used to setup the flight controller. Electronics layout is done prior to ensure a clear sight of work, components and information through the software. The flight controller used is called Pixhawk which is an open hardware mainly used for drone. The radio control system is also setup to be used as the link to control the flight controller. Flight tests were also performed to study the behavior of the drone at various percentage of throttle. At 60 percent throttle, the drone yaws continously to the left at 63.43 degrees at 4.879 degrees per second during test flights. With a payload weight of 516g, it tilted to the front nose down, with support provided at the tip of the left wing. With more design and calibration advancements, experimental findings that are similar to theoretical outcomes might be attained. Flight data after each test flight is extracted from the software and analysed for further improvement. The fabrication of complete prototype could not be finished within the stipulated time due to a delay in acquiring new parts such as propeller due to a problem, as well as procuring the appropriate material for the wing. A test of the drone motions including roll, pitch, and yaw, is also carried out using flight charts to validate the suggested design parameter. The drone tends to fly better with the motor turning with the same orientation rather than turning with different orientation due to better stability.This flight chart allows users to choose the best design parameters by determining the length of the wingspan, motor RPM, and propeller diameter that are expected to meet the performance requirements in these three flying motions. The procedure for estimating the drone's battery usage has also been presented in the flight chart.", "keywords": [ "Drone", "Throttle", "Payload (computing)", "Software", "Controller (irrigation)", "Flight test", "Simulation", "Engineering", "Fixed wing", "Computer science", "Airplane", "Automotive engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://publisher.uthm.edu.my/ojs/index.php/paat/article/download/10979/5181/53067" }, { "id": "https://openalex.org/W7124317793", "doi": "10.65109/tymt8044", "title": "MiKe: Task Scheduling for UAV-based Parcel Delivery", "year": 2024, "publication_date": "2024-05-06", "type": "conference-paper", "language": "en", "authors": [ "Viviana Arrigoni", "Giulio Attenni", "Novella Bartolini", "Matteo Finelli", "Gaia Maselli" ], "first_author": "Viviana Arrigoni", "venue": null, "publisher": null, "abstract": "Unmanned aerial vehicle (UAV) networks represent an ecological alternative to truck-based delivery systems, especially in urban areas prone to traffic congestion. In this paper, we formalize MiKe as the problem of assigning deliveries to a fleet of drones to minimize the time makespan. We solve this problem with a polynomial-time algorithm, P&D, which outperforms other state-of-the-art solutions.", "keywords": [ "Scheduling (production processes)", "Drone", "Task (project management)", "Job shop scheduling" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dl.acm.org/doi/pdf/10.5555/3635637.3663086?download=true" }, { "id": "https://openalex.org/W7160501516", "doi": "10.1142/s2301385028500203", "title": "Operational Optimization in Low-Altitude Economy: Integrated Model and Algorithm for Collaborative Vehicle-Drone Delivery", "year": 2026, "publication_date": "2026-05-08", "type": "article", "language": "en", "authors": [ "Zi X. Li", "Bin Xin", "Qing Wang", "Jia Zhang" ], "first_author": "Zi X. Li", "venue": "Unmanned Systems", "publisher": "World Scientific", "abstract": "This study develops an integrated optimization model for vehicle-drone collaborative delivery in low-altitude logistics, incorporating heterogeneous social vehicles via a dynamic quotation and negotiation process. A hybrid heuristic framework combining mixed-integer programming and event-driven simulation is proposed to handle dynamic vehicle availability and pricing uncertainty. The approach coordinates dynamic pricing, capacity-aware grouping, and cost-sensitive routing decisions, effectively balancing delivery efficiency with operational costs to maximize profit in time-sensitive last-mile distribution.", "keywords": [ "Dynamic programming", "Heuristic", "Negotiation", "Profit (economics)", "Vehicle routing problem", "Routing (electronic design automation)", "Optimization algorithm" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1142/s2301385028500203" }, { "id": "https://openalex.org/W7213338556", "doi": "10.32782/2521-6473.2026-3.17", "title": "LEGAL REGULATION OF UAV USE IN SUPPLY CHAINS AND “LAST-MILE” DELIVERY IN POSTWAR UKRAINE IN THE CONTEXT OF BALANCING PRIVATE AND PUBLIC INTERESTS", "year": 2026, "publication_date": "2026-09-15", "type": "article", "language": null, "authors": [ "A. S. Pohurelskyi" ], "first_author": "A. S. Pohurelskyi", "venue": "Legal position", "publisher": null, "abstract": "ПРАВОВЕ РЕГУЛЮВАННЯ", "keywords": [ "Context (archaeology)", "Supply chain", "Key (lock)", "Supply chain management" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.32782/2521-6473.2026-3.17" }, { "id": "https://openalex.org/W7127178631", "doi": "10.1007/978-3-032-15579-5_18", "title": "Algorithm-Enhanced Subsidy Optimization for Drone Delivery in New Retail: A Data-Governance Framework", "year": 2026, "publication_date": "2026-01-01", "type": "conference-paper", "language": "en", "authors": [ "Yiting Wang", "J. Chen", "Jingyu Xue" ], "first_author": "Yiting Wang", "venue": "Communications in computer and information science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Leverage (statistics)", "Subsidy", "Orchestration", "Drone", "Reinforcement learning", "Executable", "Supply chain", "Graph" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-032-15579-5_18" }, { "id": "https://openalex.org/W7168360639", "doi": "10.1109/iccworkshops63917.2026.11586434", "title": "Where is My Drone Delivery? Towards Multi-Actor Threat Modelling for Autonomous Delivery Systems", "year": 2026, "publication_date": "2026-05-24", "type": "conference-paper", "language": "en", "authors": [ "Elia Nikolaou", "David Aspinall" ], "first_author": "Elia Nikolaou", "venue": null, "publisher": null, "abstract": "Autonomous uncrewed aerial vehicles (UAVs) are increasingly proposed for the last-mile delivery, where security, safety, and environmental effects interact in a single operational setting. Such deployments are inherently multi-actor with crossdomain interactions. Current threat-modelling formalisms provide structured views of attacks, failures, and countermeasures but are often applied in isolation and rely on assumptions that may not hold in open, dynamic environments. In this paper, we present an initial step towards a unified semantic basis for interpreting such models via a risky world, a labelled transition system populated by interacting originators (actors) with potentially conflicting objectives. Threat models are interpreted as partial views by restricting world paths to selected originators, yielding a validity relation that characterises when a model describes the world behaviour. This enables principled comparisons of threat models across domains and makes explicit the assumptions under which their conclusions hold. Using a drone-delivery scenario, we illustrate how attacker, defender and environmental models relate to the same world and show that a threat model validated in isolation can be invalidated by cross-interactions. These results motivate joint representation. We do not provide a new threat-modelling paradigm, but a semantic bridge for future exploration connecting multiple methods.", "keywords": [ "Drone", "Key (lock)", "Action (physics)", "Field (mathematics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.research.ed.ac.uk/files/681311757/NikolaouAspinallICCWorkshops2026WhereisMyDroneDelivery.pdf" }, { "id": "https://openalex.org/W3202090826", "doi": "10.1145/3477084.3484952", "title": "SOSChain", "year": 2021, "publication_date": "2021-10-07", "type": "conference-paper", "language": "en", "authors": [ "Sahaya Beni Prathiba", "Gunasekaran Raja", "Sudha Anbalagan", "Renuka Narayanan", "K. Bhavani Venkata Karthik" ], "first_author": "Sahaya Beni Prathiba", "venue": null, "publisher": null, "abstract": "Global climate change has led to a steep rise in natural disasters. In these times, it is essential to provide emergency last-mile delivery to disaster-affected populations using connected delivery trucks; however, this gives rise to several challenges. There is an unpredictable demand for resources and the need for fault-tolerant path planning in case the trucks are subjected to attack or breakdowns. There is also the need to track resources to ensure no theft or maldistribution during critical situations. To achieve these objectives, we use a hybrid UAV-Truck architecture for last-mile relief distribution. To increase the delivery operation's robustness, we propose a Self-Optimizing StreamChain (SOSChain) that tracks and controls the status of trucks and their onboard resources. During failure scenarios, the use of information in the SOSChain enables other vehicles to optimally re-route and redistribute resources from damaged vehicles. Extensive simulation shows that SOSChain achieves over 25% improvement in throughput and up to 50% reduction in ordering latency compared to StreamChain approach in a simulated disaster environment with up to 50% vehicle failure rate.", "keywords": [ "Truck", "Robustness (evolution)", "Computer science", "Fault tolerance", "Natural disaster", "Mile", "Architecture", "Transport engineering", "Last mile (transportation)", "Failure rate", "Engineering", "Automotive engineering" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1145/3477084.3484952" }, { "id": "https://openalex.org/W7161013864", "doi": "10.1007/978-3-032-19167-0_44", "title": "A Route Optimization for a New Concept of Last Mile Delivery by Using of Autonomous Robots and Artificial Intelligence", "year": 2026, "publication_date": "2026-01-01", "type": "conference-paper", "language": "en", "authors": [ "Bartolomeo Silvestri", "Luigi Ranieri", "Agostino Marcello Mangini", "Gaetano Volpe" ], "first_author": "Bartolomeo Silvestri", "venue": "Springer proceedings in mathematics & statistics", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Robot", "Robotics", "Mobile robot", "Key (lock)", "Automation" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-032-19167-0_44" }, { "id": "https://openalex.org/W7120052815", "doi": "10.5281/zenodo.18153137", "title": "LOGISTICS DRONES", "year": 2026, "publication_date": "2026-01-05", "type": "article", "language": null, "authors": [ "David Padi and Janet O. Sadiku Matthew N. O. Sadiku" ], "first_author": "David Padi and Janet O. Sadiku Matthew N. O. Sadiku", "venue": "INTERNATIONAL JOURNAL OF ADVANCED SCIENTIFIC AND TECHNICAL RESEARCH", "publisher": null, "abstract": "ABSTRACT Drones, also known as unmanned aerial vehicles (UAVs), are very small aircraft operated without the presence of a human pilot onboard. Technology has brought great transformation into various logistics sectors such as agricultural, healthcare, education, surveillance and disaster response. Logistics drones involve delivering packages or goods from point A to point B using aerial routes rather than conventional road networks. UAVs are used for faster, cost-effective, and efficient delivery, especially for \"last-mile\" transport, by bypassing traffic for direct routes and reducing carbon footprints. They help reduce operational costs by providing faster delivery anytime, anywhere. The drone market is expected to make waves in the operations of supply chains as more enterprises prioritize efficiency in each step of the supply chain process. Soon, drone-based deliveries will be a staple. This paper explores the various uses of logistics drones. Key Words: drones, unmanned aircraft, unmanned aerial vehicles (UAVs), unmanned aircraft systems (UAS), logistics, logistics drones, supply chain, transportation", "keywords": [ "Drone", "Supply chain", "Key (lock)", "Point (geometry)", "Humanitarian Logistics", "Traffic management" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.18153137" }, { "id": "https://openalex.org/W4406073784", "doi": "10.4230/lipics.fsttcs.2024.17", "title": "Two Results on LPT: A Near-Linear Time Algorithm and Parcel Delivery Using Drones", "year": 2024, "publication_date": "2024-01-01", "type": "preprint", "language": "en", "authors": [ "L. Sunil Chandran", "Rishikesh R. Gajjala", "Mehra, Shravan", "Saladi Rahul" ], "first_author": "L. Sunil Chandran", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "The focus of this paper is to increase our understanding of the Longest Processing Time First (LPT) heuristic. LPT is a classical heuristic for the fundamental problem of uniform machine scheduling. For different machine speeds, LPT was first considered by Gonzalez et al (SIAM J. Computing, 1977). Since then, extensive work has been done to improve the approximation factor of the LPT heuristic. However, all known implementations of the LPT heuristic take $O(mn)$ time, where $m$ is the number of machines and $n$ is the number of jobs. In this work, we come up with the first near-linear time implementation for LPT. Specifically, the running time is $O((n+m)(\\log^2{m}+\\log{n}))$. Somewhat surprisingly, the result is obtained by mapping the problem to dynamic maintenance of lower envelope of lines, which has been well studied in the computational geometry community. Our second contribution is to analyze the performance of LPT for the Drones Warehouse Problem (DWP), which is a natural generalization of the uniform machine scheduling problem motivated by drone-based parcel delivery from a warehouse. In this problem, a warehouse has multiple drones and wants to deliver parcels to several customers. Each drone picks a parcel from the warehouse, delivers it, and returns to the warehouse (where it can also get charged). The speeds and battery lives of the drones could be different, and due to the limited battery life, each drone has a bounded range in which it can deliver parcels. The goal is to assign parcels to the drones so that the time taken to deliver all the parcels is minimized. We prove that the natural approach of solving this problem via the LPT heuristic has an approximation factor of $ϕ$, where $ϕ\\approx 1.62$ is the golden ratio.", "keywords": [ "Drone", "Computer science", "Algorithm" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2407.16323" }, { "id": "https://openalex.org/W7138943464", "doi": "10.2139/ssrn.6428718", "title": "Drone Delivery of Ready-to-Use Therapeutic Food and Child Malnutrition in Rwanda: An Impact Evaluation", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Olga Lebed", "Munyemana Gilbert", "Pierre Kayitana", "Maria Jose Ospina-Fadul", "Richard Nduwayezu", "Stefan Jansen", "Pedro Kremer" ], "first_author": "Olga Lebed", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Malnutrition", "Anemia", "Severe Acute Malnutrition", "Program evaluation", "Impact evaluation", "Public health", "Health facility", "Agency (philosophy)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.6428718" }, { "id": "https://openalex.org/W3186898901", "doi": "10.1109/infocomwkshps51825.2021.9484505", "title": "GenPath - A Genetic Multi-Round Path Planning Algorithm for Aerial Vehicles", "year": 2021, "publication_date": "2021-05-10", "type": "conference-paper", "language": "en", "authors": [ "Novella Bartolini", "Andrea Coletta", "Gaia Maselli", "Mauro Piva", "Domenicomichele Silvestri" ], "first_author": "Novella Bartolini", "venue": null, "publisher": null, "abstract": "The past few years have witnessed unprecedented proliferation of Unmanned Aerial Vehicles (UAVs). They are employed in a growing number of scenarios, from parcel delivery to search and rescue operations, requiring coordinated missions of a fleet of drones. Recently, there has been growing interest in optimized techniques to assign tasks and related trajectories to drones. While these techniques promise high coverage of inspected area, their applicability in real scenarios is precluded by unconsidered constraints. Among these, the limited amount of power of UAVs, and the consequent need of performing multiple trips to provide complete monitoring coverage, with battery replacement/charging and data offloading in between. To address this problem we develop Gen-Path, a genetic algorithm for efficient scheduling of multi-round UAV missions, under several objective functions. By means of simulations we show that Gen-Path fits various scenarios, improving existing solutions in terms of covered points, and energetic cost.", "keywords": [ "Drone", "Computer science", "Motion planning", "Scheduling (production processes)", "Genetic algorithm", "TRIPS architecture", "Path (computing)", "Real-time computing", "Operations research", "Mathematical optimization", "Engineering", "Artificial intelligence" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/infocomwkshps51825.2021.9484505" }, { "id": "https://openalex.org/W7110491881", "doi": null, "title": "An Analysis of New Technologies In Last-Mile Logistics Examined Through the Triple Bottom Line (TBL)", "year": 2025, "publication_date": "2025-04-01", "type": "article", "language": null, "authors": [ "Appel, Owen M." ], "first_author": "Appel, Owen M.", "venue": "ScholarWorks - GVSU (Grand Valley State University)", "publisher": "Grand Valley State University", "abstract": "Last-mile delivery is responsible for nearly half of delivery related costs and emissions. Increasing the efficiency in this segment of the supply chain is vital for companies looking to reduce waste and increase productivity to meet rising e-commerce and package delivery demand. This paper explores new technologies within last-mile delivery through the lens of the Triple Bottom Line (TBL), analyzing economic, environmental, and social implications. Technologies discussed include fleet modernization & electrification, autonomous vehicles, parcel lockers, drones, and crowdshipping. The paper primarily builds its case around the United States Postal Service (USPS), as it has been unprofitable for an extended period. Perhaps some of the findings here can shed light on how USPS can move forward.", "keywords": [ "Emerging technologies", "Productivity", "Supply chain", "Modernization theory", "Triple bottom line", "Line (geometry)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://scholarworks.gvsu.edu/cgi/viewcontent.cgi?article=1962&context=honorsprojects" }, { "id": "https://openalex.org/W7119575347", "doi": "10.5281/zenodo.18153138", "title": "LOGISTICS DRONES", "year": 2026, "publication_date": "2026-01-05", "type": "article", "language": null, "authors": [ "David Padi and Janet O. Sadiku Matthew N. O. Sadiku" ], "first_author": "David Padi and Janet O. Sadiku Matthew N. O. Sadiku", "venue": "INTERNATIONAL JOURNAL OF ADVANCED SCIENTIFIC AND TECHNICAL RESEARCH", "publisher": null, "abstract": "ABSTRACT Drones, also known as unmanned aerial vehicles (UAVs), are very small aircraft operated without the presence of a human pilot onboard. Technology has brought great transformation into various logistics sectors such as agricultural, healthcare, education, surveillance and disaster response. Logistics drones involve delivering packages or goods from point A to point B using aerial routes rather than conventional road networks. UAVs are used for faster, cost-effective, and efficient delivery, especially for \"last-mile\" transport, by bypassing traffic for direct routes and reducing carbon footprints. They help reduce operational costs by providing faster delivery anytime, anywhere. The drone market is expected to make waves in the operations of supply chains as more enterprises prioritize efficiency in each step of the supply chain process. Soon, drone-based deliveries will be a staple. This paper explores the various uses of logistics drones. Key Words: drones, unmanned aircraft, unmanned aerial vehicles (UAVs), unmanned aircraft systems (UAS), logistics, logistics drones, supply chain, transportation", "keywords": [ "Drone", "Supply chain", "Key (lock)", "Point (geometry)", "Humanitarian Logistics", "Traffic management" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.18153138" }, { "id": "https://openalex.org/W7127563085", "doi": "10.1109/gcat66372.2025.11368494", "title": "Hybrid ORB-SLAM2 Framework for Real-Time Autonomous Navigation in Urban Drone Delivery Systems", "year": 2025, "publication_date": "2025-10-24", "type": "conference-paper", "language": null, "authors": [ "RVS Praveen" ], "first_author": "RVS Praveen", "venue": null, "publisher": null, "abstract": "With more and more people living in cities around the world, urban drone delivery has changed the game for last-mile logistics. While companies like Google, Amazon, and UPS do have remarkable drone systems, they are primarily used in less populated or rural regions where navigation is not an issue. Autonomous navigation is challenging in urban environments because of the thick and intricate buildings present. Improving the precision of drone drop-offs at designated areas is the goal of this research, which suggests an image-based classification algorithm designed for cityscapes. The ability to extract features from scenes with high confidence is made possible by texture-based approaches and edge detection. By combining information from multiple sensors, multi-sensor fusion enhances the precision of localization. An organized urban area can be navigated by the system using geometric signals derived from line surface attributes and Manhattan Frame modelling. Through its development on the ORBSLAM2 framework, the proposed solution achieves an accuracy level of 98.18%, surpassing that of existing models. Autonomous navigation and contemporary logistics stand to gain from this method's potential to increase the precision, scalability, and dependability of urban drone deliveries.", "keywords": [ "Drone", "Frame (networking)", "Navigation system", "Enhanced Data Rates for GSM Evolution", "Dependability", "Line (geometry)", "Motion planning" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/gcat66372.2025.11368494" }, { "id": "https://openalex.org/W7171306492", "doi": "10.3724/sp.j.1249.2026.04468", "title": "Influencing factors of urban drone delivery choice behavior in the context of the low-altitude economy", "year": 2026, "publication_date": "2026-07-01", "type": "article", "language": "en", "authors": [ "Liao Wang", "Deng Jingrou", "Li Tao" ], "first_author": "Liao Wang", "venue": "JOURNAL OF SHENZHEN UNIVERSITY SCIENCE AND ENGINEERING", "publisher": "Science Press", "abstract": "Driven by the development of the low-altitude economy, drone delivery has emerged as a new driver for upgrading urban logistics systems. To investigate urban residents' preferences and decision-making mechanisms regarding drone delivery services, this study takes Shenzhen, China, as a case study. Based on random utility theory, revealed preferences (RP) and stated preferences (SP) surveys are conducted, and discrete choice models are employed to examine the effects of key factors on residents' actual choice behavior towards drone delivery services and the associated value conversion. The results show that residents exhibit risk-averse decision-making characteristics, and factors including safety, delivery cost, delivery time, and noise significantly influence the acceptance of drone delivery. Although variables such as gender, residential floor level, and residential location do not show significant main effects, their interaction effects with delivery cost and safety are significant, indicating that individual characteristics affect acceptance through interaction mechanisms. The effects of different factors vary substantially: safety and delivery cost have the greatest impacts on residents' choice behavior, followed by delivery time, while noise has the weakest effect. Furthermore, residents demonstrate different levels of sensitivity to these factors, with scenarios characterized by high safety and low delivery fees being the most attractive. Therefore, improving delivery safety and controlling delivery costs are essential for enhancing public acceptance of drone delivery, while differentiated strategies should be developed according to the distinct characteristics of different population groups.", "keywords": [ "Drone", "Context (archaeology)", "Population", "Discrete choice", "Affect (linguistics)", "Cost–benefit analysis" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3724/sp.j.1249.2026.04468" }, { "id": "https://openalex.org/W7147101113", "doi": "10.71443/9789349552203-16", "title": "Retail and E-Commerce Drone Delivery Systems Using AI, Cloud Computing, and Logistics Optimization", "year": 2026, "publication_date": "2026-03-30", "type": "book-chapter", "language": null, "authors": [ "Prarthana Joshi", "Subhasheni A" ], "first_author": "Prarthana Joshi", "venue": null, "publisher": null, "abstract": "The integration of drone technology into retail and e-commerce delivery systems has revolutionized the logistics sector, offering unprecedented advantages in terms of speed, efficiency, and cost reduction. This chapter explores the multifaceted role of Artificial Intelligence (AI), Cloud Computing, and Logistics Optimization in enhancing the performance of drone-based delivery systems. The focus is on key technological advancements that drive the efficiency, safety, and scalability of drone operations, particularly in the context of last-mile delivery. AI algorithms enable real-time route optimization, predictive analytics, and autonomous decision-making, while cloud platforms provide seamless coordination and management of drone fleets across diverse operational environments. Despite the significant potential, challenges related to regulatory frameworks, data security, and consumer privacy persist, requiring innovative solutions for safe and secure integration into commercial airspace. The chapter delves into the complexities of optimizing payloads and delivery speeds, addressing regulatory and ethical concerns, and ensuring robust data protection mechanisms. By evaluating current trends and future opportunities, this work provides insights into the strategic implications of adopting drone delivery systems for global supply chains, with a focus on enhancing customer experience and operational efficiency.", "keywords": [ "Drone", "Cloud computing", "Context (archaeology)", "Key (lock)", "Scalability", "Supply chain", "Work (physics)", "Focus (optics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.71443/9789349552203-16" }, { "id": "https://openalex.org/W7127051721", "doi": "10.1117/12.3101973", "title": "A 3D obstacle avoidance and path optimization method for urban logistics drones based on the A* algorithm", "year": 2026, "publication_date": "2026-02-01", "type": "conference-paper", "language": null, "authors": [ "Guoyan Che", "Xiyuan Zhang", "Jinkun Li", "Dasong Su", "Mingyang Du", "Zhiming Xu", "Yuanqing Liu", "Guan Lian" ], "first_author": "Guoyan Che", "venue": null, "publisher": null, "abstract": "With the rapid development of low-altitude economy and urban logistics transportation, an increasing number of cities are deploying logistics drones for “last-mile” delivery. However, the complex and dynamic urban low-altitude environment poses significant challenges, making autonomous obstacle avoidance and path planning during drone flight critical technical hurdles that require urgent breakthroughs. A three-dimensional obstacle avoidance and path optimization method for urban logistics drones based on an improved A* algorithm is proposed. By constructing a flight trajectory planning model that integrates safety altitude constraints with spatial distribution characteristics of obstacles, and introducing directional reward factors to enhance the search orientation of the A* algorithm, the method improves the rationality of path planning and flight safety. Simulation data validation demonstrates that the proposed method effectively generates smooth, safe, and operationally viable 3D flight paths. This research provides reliable technical support for the safe and efficient operation of logistics drones in complex urban environments.", "keywords": [ "Drone", "Obstacle avoidance", "Obstacle", "Motion planning", "Path (computing)", "Trajectory" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1117/12.3101973" }, { "id": "https://openalex.org/W4415480015", "doi": "10.2139/ssrn.5648580", "title": "Slope-Aware Energy Optimization for Cooperative Truck–Drone Delivery and Pickup Routing with Time Windows", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": null, "authors": [ "Ying Wang", "Taofeng Ye", "Jiajun Sun", "Jicong Duan" ], "first_author": "Ying Wang", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Pickup", "Benchmark (surveying)", "Terrain", "Energy consumption", "Routing (electronic design automation)", "Drone", "Vehicle routing problem", "Energy (signal processing)", "Sensitivity (control systems)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5648580" }, { "id": "https://openalex.org/W4415902834", "doi": "10.2139/ssrn.5705648", "title": "Slope-Aware Energy Optimization for Cooperative Truck–Drone Delivery and Pickup Routing with Time Windows", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": null, "authors": [ "Ying Wang", "Taofeng Ye", "Jiajun Sun", "Jicong Duan" ], "first_author": "Ying Wang", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Pickup", "Benchmark (surveying)", "Terrain", "Energy consumption", "Routing (electronic design automation)", "Drone", "Vehicle routing problem", "Energy (signal processing)", "Sensitivity (control systems)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5705648" }, { "id": "https://openalex.org/W4383375890", "doi": "10.17825/klr.2023.33.3.30", "title": "Analysis and Forecast of Patent Trends in Unmanned Delivery Robot Technology: Focusing on Last-Mile Delivery Technology", "year": 2023, "publication_date": "2023-06-30", "type": "article", "language": "en", "authors": [ "Tae-Men Kim", "Bo-Na Choi", "Chan-Jeong Park" ], "first_author": "Tae-Men Kim", "venue": "한국물류학회지", "publisher": null, "abstract": "With the advent of the untact era due to COVID-19, demand in the existing online market and the courier and logistics industry is accelerating. At the same time, the problem of decreasing available labor force due to decreasing population growth rate and aging is growing, causing difficulties due to labor shortage. In this paper, we examine the patent application trends of unmanned delivery systems by country, technology, and major applicants, and identify the degree of patent activity of major companies through index analysis. To this end, we analyzed domestic and foreign patents on unmanned delivery robot technology filed up to July 2021, and classified them according to the technology classification system to present the outlook of unmanned delivery technology. The analysis showed that robots, drones, and unmanned delivery boxes, which combine IoT technologies of the Fourth Industrial Revolution based on last-mile delivery technology, are expanding their scope of use. In addition, the development of cooperative delivery services combining robots and drones is expected, and the differentiation of delivery costs between rapid delivery by drones and regular delivery by robots is expected. This paper is expected to raise awareness of unmanned delivery technology among related companies and researchers, and to serve as a reference for future research and development for efficient last-mile delivery", "keywords": [ "Drone", "Last mile (transportation)", "Economic shortage", "Delivery system", "Technology development", "Population", "Scope (computer science)", "Business", "Operations management", "Engineering", "Computer science", "Mile" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.17825/klr.2023.33.3.30" }, { "id": "https://openalex.org/W4416550482", "doi": "10.2139/ssrn.5789201", "title": "Value creation through disruptive technologies to mitigate complaints in last-mile deliveries during crisis", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": null, "authors": [ "Yaşanur Kayıkçı", "Nachiappan Subramanian", "Özgür Kabadurmuş" ], "first_author": "Yaşanur Kayıkçı", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Operational excellence", "Competitive advantage", "Customer satisfaction", "Supply chain", "Supplier relationship management", "Resilience (materials science)", "Customer engagement", "Service recovery", "Service provider", "Service quality", "Service (business)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5789201" }, { "id": "https://openalex.org/W2998624134", "doi": "10.6036/9400", "title": "LOGISTICS INNOVATION: STARTUPS AND NEW BUSINESS MODELS", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Diéssica de Oliveira Dias", "Juan Manuel Maqueira Marín", "Sebastián Bruqué Cámara", "José Moyano‐Fuentes" ], "first_author": "Diéssica de Oliveira Dias", "venue": "DYNA", "publisher": "National University of Colombia", "abstract": "In order to solve the last mile problem, several startups are developing systems to transform the way products are distributed and delivered. Among the innovations they use are unmanned aerial vehicles, known as drones, or automated delivery points, known as Pick Up and Drop Off systems.", "keywords": [ "Drone", "Last mile (transportation)", "Order (exchange)", "Business", "Drop (telecommunication)", "Business model", "Computer science", "Industrial organization", "Mile", "Marketing", "Telecommunications", "Finance" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.6036/9400" }, { "id": "https://openalex.org/W7172441567", "doi": "10.1007/978-3-032-14397-6_1", "title": "Public Acceptance of Drone Delivery Services from Convenience Stores: A Case Study in South Korea", "year": 2026, "publication_date": "2026-01-01", "type": "book-chapter", "language": "en", "authors": [ "Woosik Jeong", "Kunwoo Lee", "KwangSup Shin", "Woojung Kim" ], "first_author": "Woosik Jeong", "venue": "Studies in computational intelligence", "publisher": "Springer Nature", "abstract": null, "keywords": [ "Drone", "Affect (linguistics)", "Preference", "Discrete choice", "Willingness to pay", "Externality" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-032-14397-6_1" }, { "id": "https://openalex.org/W2551831851", "doi": "10.1145/2999504.3001103", "title": "Operational conditions of an unmanned aerial vehicle (UAV) based underwater data collection system", "year": 2016, "publication_date": "2016-01-01", "type": "conference-paper", "language": "en", "authors": [ "Shengming Jiang", "Yao Nan", "Xinlei Jin" ], "first_author": "Shengming Jiang", "venue": null, "publisher": null, "abstract": "The last mile data transport from surface units to terrestrial data processing centers now is mainly carried out by either manual collection with manned ships or satellite networks, neither of which is cost-effective. Recently, several proposals discuss UAV-based solutions in terms of the design and testing of communication and networking. Due to unique geographical and climatic conditions in the ocean, this paper discusses constraints for a UAV to complete a data collection mission without landing in water or crashing.", "keywords": [ "Data collection", "Underwater", "Computer science", "Mile", "Last mile (transportation)", "Remote sensing", "Marine engineering", "Aeronautics", "Satellite", "Remotely operated underwater vehicle", "Systems engineering", "Environmental science" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1145/2999504.3001103" }, { "id": "https://openalex.org/W7171557086", "doi": "10.12677/ecl.2026.157834", "title": "Delivery Route Optimization for E-Commerce Last-Mile Logistics in the Era of Low-Altitude Economy", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": null, "authors": [ "Dongxuan Xiao" ], "first_author": "Dongxuan Xiao", "venue": "E-Commerce Letters", "publisher": null, "abstract": "在低空经济快速崛起、电商物流配送向智能化、无人化升级的背景下，无人机作为低空物流的核心载体，其路径规划的合理性直接影响电商末端配送的效率、成本与安全性，更是推动低空经济与电子商务深度融合的关键技术支撑。本文针对电商末端物流配送场景下的三维无人机路径规划问题，以飞行距离、高度变化、安全和平滑性为核心约束条件，构建多目标成本函数并设计改进淘金优化算法(IGRO)用于寻找最优配送路径。通过仿真实验验证IGRO相较于原淘金优化算法，路径规划总成本平均减少40.1%。且相较于其他对比算法，不仅具备最优的路径规划效果，还拥有最快的收敛速度，充分证明本文构建的路径规划模型与改进算法的有效性和实用性，助力打通低空经济背景下电商末端配送最后一公里瓶颈。Against the backdrop of the rapid rise of the low-altitude economy and the upgrading of e-commerce logistics distribution towards intelligence and unmanned operation, drones, as the core carrier of low-altitude logistics, their reasonable path planning directly determines the efficiency, cost and safety of e-commerce terminal distribution, and is also a key technical support for promoting the in-depth integration of the low-altitude economy and e-commerce. Aiming at the 3D UAV path planning problem in the scenario of e-commerce terminal logistics distribution, this paper takes flight distance, flight altitude, flight safety and smoothness as the core constraints, constructs a multi-objective cost function and designs an Improved Gold Rush Optimization algorithm (IGRO) to find the optimal distribution path. Simulation experiments verify that compared with the original Gold Rush Optimization (GRO) algorithm, the total path planning cost of the IGRO algorithm is reduced by an average of 40.1%. Moreover, compared with other comparative algorithms, it not only has the optimal path planning effect, but also has the fastest convergence speed, which fully proves the effectiveness and practicality of the path planning model and improved algorithm constructed in this paper, helping to break through the bottleneck of the last mile in e-commerce terminal distribution under the background of the low-altitude economy.", "keywords": [ "Path (computing)", "Bottleneck", "Smoothness", "Convergence (economics)", "Key (lock)", "Core (optical fiber)", "Terminal (telecommunication)", "Function (biology)", "Sequence (biology)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://pdf.hanspub.org/ecl_2319069.pdf" }, { "id": "https://openalex.org/W3187594464", "doi": "10.1109/cec45853.2021.9504975", "title": "Fast Heuristics for Traveling Salesman Problems with Multiple Flying Sidekicks", "year": 2021, "publication_date": "2021-06-28", "type": "conference-paper", "language": "en", "authors": [ "Gustavo Delazeri", "Marcus Ritt" ], "first_author": "Gustavo Delazeri", "venue": null, "publisher": null, "abstract": "Speedy delivery of products is important for customers and the optimization of the last mile has particular challenges. In recent years drone-supported delivery has become increasingly feasible and therefore a topic of intense research. In this paper we address a traveling salesman problem where a truck has to serve customers and can use drones as flying sidekicks for the delivery of parcels. The goal is to assign customers to be either served by the truck or by some drone and schedule all events in order to minimize the total completion time of whole operation. We propose a heuristic for this problem, and introduce several novel components, including a multi-armed bandit selection for partitioning customers, an efficient matching-based heuristic for assigning drones to customers, local searches to improve solutions, and a fast greedy scheduler to estimate solution quality. In computational experiments we show that the combined approach finds better solutions than current methods, in less time.", "keywords": [ "Travelling salesman problem", "Heuristics", "Drone", "Computer science", "Heuristic", "Greedy algorithm", "Matching (statistics)", "Schedule", "Truck", "Traveling purchaser problem", "Mathematical optimization", "Operations research" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/cec45853.2021.9504975" }, { "id": "https://openalex.org/W3211931943", "doi": null, "title": "Optimization models and algorithms for unmanned aerial vehicle applications", "year": 2020, "publication_date": "2020-03-12", "type": "article", "language": "en", "authors": [ "Adriano Masone" ], "first_author": "Adriano Masone", "venue": null, "publisher": null, "abstract": "Unmanned aerial vehicles (UAVs) or drones are currently in the prominence of technology expansion of many organizations in different application fields including logistics, surveillance, security, emergency response, agriculture, and investigative science. Indeed, recent advances in unmanned vehicle technology set up new opportunities to increase the efficiency and effectiveness of drone systems that can be exploited by these organizations.\nHowever, there are many complex issues in modeling, solving, and implementing drone systems. \nThese issues constitute a topic receiving considerable attention in the last years but the operations research community has only recently started to focus on them with particular reference to the logistic applications. This thesis brings together an overview of drone technology and applications, and a state-of-the-art of the operational research contributions to the optimization of drone systems. Moreover, it presents three optimization approaches to solve problems which consider the use of a truck and a drone to exploit the advantages of both the vehicles for last-mile deliveries.", "keywords": [ "Drone", "Exploit", "Computer science", "Systems engineering", "Truck", "Operations research", "Aeronautics", "Engineering", "Computer security", "Aerospace engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://www.fedoa.unina.it/13100/" }, { "id": "https://openalex.org/W2269330484", "doi": null, "title": "UAV schemes look to go the last mile : potential commercial applications for unmanned technology on the rise, but big airspace integration challenge remains", "year": 2015, "publication_date": "2015-11-03", "type": "article", "language": "en", "authors": [ "Beth Stevenson" ], "first_author": "Beth Stevenson", "venue": "Flight international", "publisher": "DVV Media Group", "abstract": null, "keywords": [ "Aeronautics", "Mile", "Last mile (transportation)", "Engineering", "Drone", "Telecommunications", "Aerospace engineering", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://trid.trb.org/view/1387534" }, { "id": "https://openalex.org/W7164559805", "doi": "10.1016/j.jestch.2026.102434", "title": "Performance analysis of a PV powered drone delivery network under realistic solar energy constraints", "year": 2026, "publication_date": "2026-06-12", "type": "article", "language": "en", "authors": [ "Roko Bračić", "Goran Krajačić", "Marko Mimica", "Zvonimir Šoša" ], "first_author": "Roko Bračić", "venue": "Engineering Science and Technology an International Journal", "publisher": "Elsevier BV", "abstract": "As the global shipping industry aims to reduce greenhouse gas emissions by 50 % by 2050, drone delivery networks present a promising solution for last-mile logistics. However, existing studies often rely on idealized assumptions regarding energy availability, overlooking the stochastic nature of renewable energy sources. This paper presents a comprehensive performance analysis of a PV-powered drone delivery network in the North Adriatic Sea, utilizing a discrete-time, agent-based simulation model. The study integrates real-world, time-series photovoltaic generation data to evaluate system throughput, energy consumption, and charging bottlenecks over a 48-hour period. Results indicate a severe performance gap between idealized and realistic scenarios: while an ideal system achieved a 100 % success rate, the introduction of realistic solar variability reduced the success rate to 51.7 % and caused significant queuing delays totaling over 223 h. Furthermore, the study reveals a counter-intuitive finding where increasing the number of chargers per hub during low-energy periods further degraded system performance by distributing scarce energy too thinly. A scalability analysis across fleet sizes of 30 to 240 drones demonstrates that proportional PV scaling restores performance at moderate fleet sizes, but a hub topology ceiling emerges at larger scales, indicating that routing and congestion management become the binding constraints beyond a critical fleet density. These findings underscore the critical necessity of incorporating energy intermittency constraints into the design of sustainable autonomous logistics infrastructure and identify techno-economic optimization of PV sizing and hub topology as key directions for future work.", "keywords": [ "Drone", "Solar powered", "Photovoltaic system", "Solar energy", "Energy (signal processing)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jestch.2026.102434" }, { "id": "https://openalex.org/W7154493329", "doi": "10.12677/ecl.2026.154434", "title": "Smart “Last Mile” Delivery for E-Commerce O2O Platforms: Multi-Objective UAV Track Optimization Based on Deep Reinforcement Learning", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": null, "authors": [ "雨聪 李" ], "first_author": "雨聪 李", "venue": "E-Commerce Letters", "publisher": null, "abstract": null, "keywords": [ "Reinforcement learning", "Track (disk drive)", "Automation", "Artificial neural network", "Trajectory", "Control (management)", "Tracking (education)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.12677/ecl.2026.154434" }, { "id": "https://openalex.org/W7112509138", "doi": null, "title": "Novel Spherical Fuzzy MARCOS Method for Assessment of Drone-Based City Logistics Concepts", "year": null, "publication_date": null, "type": "article", "language": null, "authors": [ "Milovan KovaÄ", "Snežana Tadić", "Mladen Krstić", "Mouhamed Bayane Bouraima", "Borna Abramović" ], "first_author": "Milovan KovaÄ", "venue": "RePEc: Research Papers in Economics", "publisher": "Federal Reserve Bank of St. Louis", "abstract": "Technological innovations from the last few years, in the combination with city logistics (CL) initiatives, make the definition of novel, complex, sustainable CL solutions possible. Unmanned aerial vehicles (drones) as a technology attracted lots of attention in the literature. Various researches focused on different drone-based delivery approaches, but there are only a few articles dealing with drones as the elements of complex CL concepts. The goal of this paper is to evaluate different drone-based CL concepts. Based on the existing ideas of drone application in delivery, the main group of CL concepts and their variants are defined, which represents the main contribution of the article. The evaluation and ranking of concepts are performed from the aspect of all CL stakeholders and the defined set of criteria by applying measurement of alternatives and ranking according to compromise solution (MARCOS) multicriteria decision-making (MCDM) method in spherical fuzzy environment, which represents another contribution of the article. The results indicate that the potentially best CL concept, with the final score of 0.408, is the one that refers to the transformation of the logistics system into a two-echelon system with the implementation of micro-consolidation centers (MCCs), in which the delivery of goods to MCCs is realized with rail transportation mode and the last delivery phase with drones. It is followed by the concepts that imply MCCs, and rail transportation in the function of mobile depots for drone launching and MCCs and ground delivery vehicles (GDVs), with the final scores of 0.395 and 0.390, respectively.", "keywords": [ "Ranking (information retrieval)", "Drone", "Fuzzy logic", "Set (abstract data type)", "Function (biology)", "Fuzzy set", "Field (mathematics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://downloads.hindawi.com/journals/complexity/2021/2374955.xml" }, { "id": "https://openalex.org/W7204481209", "doi": "10.64960/easr.2026.265202", "title": "Fuzzy multimodal vehicle routing for last-mile flood relief: A scenario-based model for Chiang Mai", "year": 2026, "publication_date": "2026-08-27", "type": "article", "language": null, "authors": [ "Kanyarat Phutthanawong", "Takashi Irohara", "Israt Jahan Hridi", "Chawis Boonmee" ], "first_author": "Kanyarat Phutthanawong", "venue": "Engineering and Applied Science Research", "publisher": "Khon Kaen University", "abstract": "This research addresses the logistical challenges of last-mile relief delivery during flood disasters in Chiang Mai, Thailand. We propose a scenario-based fuzzy multi-depot, multi-trip vehicle routing problem model with split deliveries and integrated multimodal accessibility across varying flood severity levels. The model incorporates fuzzy logic to handle uncertainty by transforming it into an equivalent auxiliary crisp model through triangular membership functions. The objective function aims to minimize total transportation time across five flood scenarios. Results demonstrate that community accessibility requirements vary significantly with flood severity: low water levels can be served entirely by trucks, while severe flooding necessitates intensive boat operations, significantly increasing response times and trip frequencies. Sensitivity analysis reveals that strategic boat-drone collaboration in Scenario 4 can reduce the number of trips by 2 and travel time by up to 3.7%, while significantly simplifying boat routing complexity. The study provides actionable insights for disaster management agencies, emphasizing the critical role of scenario-based planning, multimodal fleet deployment, and robust decision-making under uncertainty.", "keywords": [ "Flood myth", "Fuzzy logic", "Flooding (psychology)", "Chiang mai", "Routing (electronic design automation)", "TRIPS architecture", "Vehicle routing problem", "Sensitivity (control systems)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ph01.tci-thaijo.org/index.php/easr/article/download/265202/176337" }, { "id": "https://openalex.org/W4295959754", "doi": "10.1016/j.cja.2022.09.009", "title": "Aerial-ground collaborative routing with time constraints", "year": 2022, "publication_date": "2022-09-15", "type": "article", "language": "en", "authors": [ "Jiahao Xing", "Lichen Su", "Wenjing HONG", "Lu Carol Tong", "Renli LYU", "Wenbo Du" ], "first_author": "Jiahao Xing", "venue": "Chinese Journal of Aeronautics", "publisher": "Elsevier BV", "abstract": "The advancement of autonomous technology makes electric-powered drones an excellent choice for flexible logistics services at the last mile delivery stage. To reach a balance between green transportation and competitive edge, the collaborative routing of drones in the air and trucks on the ground is increasingly invested in the next generation of delivery, where it is particularly reasonable to consider customer time windows and time-dependent travel times as two typical time-related factors in daily services. In this paper, we propose the Vehicle Routing Problem with Drones under Time constraints (VRPD-T) and focus on the time constraints involved in realistic scenarios during the delivery. A mixed-integer linear programming model has been developed to minimize the total delivery completion time. Furthermore, to overcome the limitations of standard solvers in handling large-scale complex issues, a space-time hybrid heuristic-based algorithm has been developed to effectively identify a high-quality solution. The numerical results produced from randomly generated instances demonstrate the effectiveness of the proposed algorithm.", "keywords": [ "Drone", "Routing (electronic design automation)", "Vehicle routing problem", "Integer programming", "Computer science", "Truck", "Heuristic", "Operations research", "Linear programming", "Enhanced Data Rates for GSM Evolution", "Last mile (transportation)", "Mathematical optimization" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S1000936122002175/pdf" }, { "id": "https://openalex.org/W7165873150", "doi": "10.1016/j.asoc.2026.115816", "title": "Dynamic multi-drone parcel delivery via cooperative multi-objective particle swarm optimization", "year": 2026, "publication_date": "2026-06-25", "type": "article", "language": "en", "authors": [ "Xinyi Zhao", "Puxi Liu", "Long Ma", "Bailing Tian" ], "first_author": "Xinyi Zhao", "venue": "Applied Soft Computing", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Particle swarm optimization", "Multi-swarm optimization", "Metaheuristic", "Minification", "Optimization problem" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.asoc.2026.115816" }, { "id": "https://openalex.org/W7154467386", "doi": "10.1109/icat2i69744.2025.11472709", "title": "Hybrid AI Framework for Energy-Efficient Last-Mile Delivery in Urban Areas: A PRISMA-Based Systematic Review", "year": 2025, "publication_date": "2025-12-25", "type": "review", "language": null, "authors": [ "Jihad Mkhalfi", "Fouad Jawab", "Imane Moufad" ], "first_author": "Jihad Mkhalfi", "venue": null, "publisher": null, "abstract": "In this article, we conduct a systematic literature review of 28 academic papers published between 2016 and 2024 about hybrid artificial intelligence systems directed towards energy efficient last-mile urban delivery activities. We examine key AI techniques - including the use of machine learning in demand forecasting and adaptive routing processes, reinforcement learning for optimizing energy consumption for last-mile delivery using electric vehicles, multi-agent systems for optimizing highly complex urban logistics, and utilizing various metaheuristic algorithms for optimizing routing and scheduling of delivery vehicles. We identified autonomous delivery that leverages drones and robots guided through Artificial Intelligence mission planning. Despite this research on hybrid artificial intelligence for energy efficient last-mile delivery activities, we found little work focused on a human-centered approach without the utilization of Artificial Intelligence. Thus, we see it as an opportunity for future investigations to improve energy efficient urban delivery simply through the improvement of non-AI based methods. We examined a contribution for hybrid AI-assisted methods to provide evidence towards an existing gap in human-centered inquiry concerning energy-efficient urban delivery activities.", "keywords": [ "Key (lock)", "Component (thermodynamics)", "Field (mathematics)", "Expert system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icat2i69744.2025.11472709" }, { "id": "https://openalex.org/W7172449836", "doi": "10.1109/jstars.2026.3720481", "title": "LLM-Augmented Spatiotemporal Occupancy-Aware Multi-UAV Scheduling Using OSM-Derived Geospatial Data for Smart-City Last-Mile Delivery", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": "en", "authors": [ "Israr Ahmad", "Shang Fengjun", "Altaf Hussain", "Tariq Hussain", "Razaz Waheeb Attar", "Amal Hassan Alhazmi" ], "first_author": "Israr Ahmad", "venue": "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Urban last-mile delivery with multi-UAV fleets is constrained not only by travel distance, but also by temporary landing-exclusion zones created during parcel drop-off. When several UAVs serve nearby delivery points, these exclusion zones can overlap in space and time, forcing hover waiting and increasing fleet makespan. A further challenge is that rooftop, ground-open, and constrained-corridor deliveries impose different landing radii and occupancy durations, while many scheduling models treat delivery points uniformly. This article proposes an OpenStreetMap (OSM) and large language model (LLM)-augmented spatiotemporal occupancy-aware multi-UAV scheduling framework for smart-city last-mile delivery. OSM building footprints, road networks, and open-space polygons are used to classify delivery points into three landing-zone types, after which representative landing-mode parameters are assigned for exclusion-aware scheduling. An LLM-based adaptive weighting mechanism (gpt-4o-mini-2024-07-18, $T=0$ ) maps zone statistics, conflict density, and urban-morphology cues to priority weights for occupancy-, distance-, and conflict-aware task ordering. Experiments on Tokyo and Shenzhen evaluate 24 configurations across two cities, three fleet sizes, four scheduling strategies, and ten random seeds. The proposed framework reduces makespan by more than 90% relative to a sequential single-trip upper bound reference, confirming the benefit of parallel fleet scheduling under landing-exclusion constraints. Against non-LLM heuristics, the LLM-Adaptive strategy remains competitive and achieves the best result in the resource-constrained Shenzhen 12-UAV case. On a reduced ten-task mixed integer linear programming benchmark solved with CPLEX 22.1 to a gap of at most 0.1%, the LLM-Adaptive strategy closes 4.3%–5.2% of the optimality gap left by the best hand-tuned heuristic at $K=3$ . The results show that OSM-derived zone classification and LLM-based priority weighting provide an interpretable and reproducible approach for exclusion-aware multi-UAV scheduling.", "keywords": [ "Geospatial analysis", "Scheduling (production processes)", "Processor scheduling", "Data modeling", "Distributed database" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/jstars.2026.3720481" }, { "id": "https://openalex.org/W7153060879", "doi": "10.47749/t/unicamp.2025.1544375", "title": "Real-time UAV path planning for last-mile delivery operations with a focus on urban safety supported by deep learning-based human detection", "year": 2025, "publication_date": "2025-12-17", "type": "dissertation", "language": null, "authors": [ "Débora Paula Simões" ], "first_author": "Débora Paula Simões", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Focus (optics)", "Motion planning", "Path (computing)", "Key (lock)", "System safety" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.47749/t/unicamp.2025.1544375" }, { "id": "https://openalex.org/W7213664087", "doi": "10.31891/2219-9365-2025-83-18", "title": "Decentralized last-mile delivery using ai and 5G: improving efficiency and speed in next-generation networks", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": "uk", "authors": [ "Ю. Я. Лещенко", "І. І. Мороз", "М. С. Юхимчук", "Yu. Ya. Leshchenko", "І. О. Мороз", "М. Yukhymchuk" ], "first_author": "Ю. Я. Лещенко", "venue": "Repository of Vinnytsia National Technical University (Vinnytsia National Technical University)", "publisher": "Vinnytsia National Technical University", "abstract": "This paper explores the integration of artificial intelligence (AI) and fifth-generation mobile networks (5G) into decentralized last-mile delivery systems, aiming to improve efficiency, scalability, and customer satisfaction. Building on previous research, which employed AI-driven optimization techniques such as genetic algorithms and real-time weather data integration, the study highlights how 5G technology can overcome existing challenges related to network latency, data transmission speed, and coordination within decentralized logistics networks. The ultra-fast data transfer rates and ultra-low latency of 5G enable real-time route optimization, dynamic fleet management, and seamless coordination between multiple delivery nodes, significantly reducing delivery times and operational costs. The paper also examines the role of AI-powered autonomous vehicles supported by 5G, which can address the shortage of couriers and enhance delivery safety and efficiency in densely populated areas. Furthermore, the research analyzes potential applications of blockchain technology in last-mile logistics, particularly in enhancing transparency, authenticity verification, and automation through smart contracts. Key technical challenges such as infrastructure costs, limited network coverage, interoperability, cybersecurity, interference, and energy consumption are also discussed, along with potential solutions including network slicing, adaptive interference management, and blockchain-based security models. The study emphasizes the future potential of combining 5G, AI, and blockchain in creating sustainable, adaptive, and customer-oriented logistics ecosystems. Promising directions include machine learning for demand prediction, on-demand and drone-based deliveries, energy optimization, and advanced indoor navigation supported by 5G. Overall, the paper argues that integrating 5G into decentralized last-mile delivery not only addresses existing limitations but also opens avenues for innovation in logistics, contributing to economic growth, environmental sustainability, and improved quality of urban life.", "keywords": [ "Key (lock)", "Efficient energy use", "Energy consumption", "Automation", "Data transmission", "Big data", "Cloud computing" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ir.lib.vntu.edu.ua/bitstream/123456789/51723/2/201535.pdf" }, { "id": "https://openalex.org/W4411025914", "doi": "10.3390/app15116322", "title": "Research on Dynamic Planning Method for Air–Ground Collaborative Last-Mile Delivery Considering Road Network Fragility", "year": 2025, "publication_date": "2025-06-04", "type": "article", "language": "en", "authors": [ "Wei Min Qi", "Ang Li", "Honghai Zhang" ], "first_author": "Wei Min Qi", "venue": "Applied Sciences", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Urban road networks are prone to disruptions that can result in localized congestion or even complete interruptions, thereby causing delays in conventional logistics distribution. To mitigate this issue, the present study proposes a dynamic deployment model and task planning methodology for vehicle–drone collaborative delivery in areas affected by road disruptions. Utilizing complex network theory, a framework for identifying node vulnerabilities within road networks is established. Furthermore, a dynamic model for selecting drone take-off and landing sites, as well as task planning, is developed with the dual objectives of minimizing delivery costs and time while maximizing demand coverage. An enhanced evolutionary algorithm is devised to address the model. Results from case studies indicate that when the failure rate of regional road network nodes reaches 50%, the network vulnerability value is 0.8, achieving an air–ground collaborative logistics task completion rate of 95% and a delivery time of approximately 120 min. Conversely, when node failure escalates to 70%, the vulnerability value approaches 1.0, while still achieving a 90% task completion rate and a delivery time of 150 min. The proposed air–ground collaborative dynamic logistics approach effectively addresses distribution challenges in disrupted road networks and offers technical support for the advancement of urban low-altitude logistics.", "keywords": [ "Fragility", "Mile", "Last mile (transportation)", "Computer science", "Transport engineering", "Engineering", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2076-3417/15/11/6322/pdf?version=1749043682" }, { "id": "https://openalex.org/W7138050235", "doi": "10.1016/j.trpro.2026.02.140", "title": "Design and multiple criteria evaluation of last mile delivery solutions for a down town area of a medium sized city", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": "en", "authors": [ "Jacek Żak", "Ali Alazzawi" ], "first_author": "Jacek Żak", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "The paper presents the development, analysis and multiple criteria evaluation of certain modern, innovative transportation/ logistics solutions for a last mile delivery system of goods in Poznan City in Poland. 9 alternative, technologically advanced “last mile” delivery concepts based on: drones, autonomous vehicles, cargo bikes, crowd shipping and freight car pooling are considered and simulated. The results of simulation constitute an input for the definition of 7 evaluation criteria of the considered solutions/ variants. Based on the evaluation of the considered variants, last mile delivery solutions are ranked from the best to the worst. Their ranking is generated in the computational phase carried out with the application of a selected Multiple Criteria Decision Making/ Aiding (MCDM/A) method (ELECTRE III/IV). The results of computational experiments are demonstrated as a ranking from the best solution to the worst and a final recommendation is provided.", "keywords": [ "Last mile (transportation)", "Mile", "Data collection" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trpro.2026.02.140" }, { "id": "https://openalex.org/W4409296335", "doi": "10.59890/ijasr.v3i3.494", "title": "Security Threats in Unmanned Aerial Vehicles Based Internet of Things", "year": 2025, "publication_date": "2025-03-29", "type": "article", "language": "en", "authors": [ "Jouma Ali Al-Mohamad" ], "first_author": "Jouma Ali Al-Mohamad", "venue": "International Journal of Applied and Scientific Research", "publisher": null, "abstract": "significant advancements in autonomous data collection and real-time decision-making. UAVs are equipped with sensors, cameras, and GPS modules that enable them to connect with IoT ecosystems for tasks like precision farming, remote sensing, and last-mile delivery. However, this integration also introduces vulnerabilities that adversaries can exploit, such as jamming, spoofing, and unauthorized data access. This section provides an overview of UAV-based IoT applications and highlights the importance of securing these systems. Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, have undergone rapid evolution over the past two decades. The advent of IoT technologies has further accelerated this growth, enabling UAVs to serve as integral components in smart environments. IoT enables drones to communicate with other devices, share data in real time, and perform complex tasks autonomously. However, this technological advancement has expanded the attack surface for malicious actors. Security measures that were sufficient for standalone UAVs are now inadequate in the context of IoT-enabled systems. This paper aims to explore the diverse security threats affecting UAV-based IoT systems, ranging from physical attacks and GPS spoofing to advanced cyber threats such as ransomware targeting drone networks. By examining the literature, highlighting real-world incidents, and analyzing emerging trends, this research provides a comprehensive overview of the challenges and solutions in securing UAVs within IoT environments", "keywords": [ "Drone", "Computer security", "Internet of Things", "The Internet", "Internet privacy", "Aeronautics", "Computer science", "Engineering", "World Wide Web" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://jurnalinternasional.com/index.php/ijasr/article/download/494/692" }, { "id": "https://openalex.org/W4312863124", "doi": "10.32628/ijsrset229463", "title": "Agricultural Based Drone", "year": 2022, "publication_date": "2022-09-01", "type": "article", "language": "en", "authors": [ "Mohd Yaser Uddin", "Mujeeb Ur Rahman", "Mohammed Anas Uddin", "Syed Aijaz Shoaib Mohd", "Shaik Sohail Ahmed", "Arshiya" ], "first_author": "Mohd Yaser Uddin", "venue": "International Journal of Scientific Research in Science Engineering and Technology", "publisher": "Technoscience Academy", "abstract": "The main vison of our project is to built a drone which can do certain things that is very much impossible by standards of a human in the fields such as locomotion and aerodynamics. The demand for delivery personnel has multiplied due to the significant growth in the use of online ordering. In order to fulfil this demand, drone-based technology is being deployed. A hexacopter can fly vertically in a stable manner and be used to deliver goods or collect data in a certain area. We think delivery drones are poised to disrupt the last mile transportation industry given the development of drone technology and rising commercial usage. Drones can drastically shorten delivery times and lower the cost of delivery for both humans and drone manufacturers.. The value chain and opportunities in the market for delivery drones are examined in this paper. It also talks about adoption's difficulties. Our argument for using drones to deliver the majority of lightweight products for the final mile comes at the end. This study describes the Hexa copter (QC) as a lightweight, inexpensive, autonomous flying capable Unmanned Aerial Vehicle (UAV) for delivering packages ordered online. Its primary on-board computing unit is an android device. This QC can locate and reach its goal by using Google Maps. This experiment showcases QC's ability to deliver an online-ordered package and then return to the starting point. Future studies on the use of QC for parcel delivery are made possible by the method's encouraging results.", "keywords": [ "Drone", "Computer science", "Android (operating system)", "Last mile (transportation)", "Mile", "Aeronautics", "Engineering", "Computer security", "Simulation", "Operating system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.32628/ijsrset229463" }, { "id": "https://openalex.org/W2907928286", "doi": "10.1109/liss.2018.8593214", "title": "Concepts for Cargo Ground Handling of Unmanned Cargo Aircrafts and Their Influence on the Supply Chain", "year": 2018, "publication_date": "2018-08-01", "type": "conference-paper", "language": "en", "authors": [ "Peter Meincke", "Lukas Asmer", "Leonard Geike", "Hendrik Wiarda" ], "first_author": "Peter Meincke", "venue": null, "publisher": null, "abstract": "The steadily growing share of air freight transport in the entire logistics industry is mainly due to the three major advantages of speed, safety and reliability. To meet the rising demands, automated transport and delivery processes are increasingly used. As part of the DLR (German Aerospace Center) research project Automated Low Altitude Delivery (ALAADy), a fully automated Unmanned Cargo Aircraft (UCA) with a payload of one ton under the precondition of the Minimum Risk Configuration is being developed. The theoretical and practical concepts of this topic were examined within the study under the premise that “No infrastructure exits at destination” in order to obtain the most automated process possible for future logistics. Our study shows that the interaction between an UCA and an automated robotic container-system solves both problems of the penultimate and the last mile within the logistics chain. Furthermore, the concepts of ground handling and the development of unmanned systems, including their present capabilities, were studied theoretically to design a model representing basic ground handling processes of Unmanned Aircraft Vehicles (UAVs). The intention was to create a base for further research on this matter by targeting the key requirements for ground handling processes of UCAs in the given concepts. We found out that our obtained findings, approaches for an automated turnaround of an UAV can therefore serve as a basis for future analyses in UCA ground handling and last miles logistics.", "keywords": [ "Payload (computing)", "Supply chain", "Aerospace", "Process (computing)", "Automation", "Drone", "Systems engineering", "Last mile (transportation)", "Computer science", "Key (lock)", "Container (type theory)", "Engineering" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/liss.2018.8593214" }, { "id": "https://openalex.org/W7165734464", "doi": "10.1109/icns69853.2026.11570447", "title": "Parcel delivery with drones and U-space: A case study on airside traffic flow, environmental and societal effects", "year": 2026, "publication_date": "2026-04-14", "type": "conference-paper", "language": null, "authors": [ "Teemu Joonas Lieb", "Niklas Peinecke", "Gunnar Schwoch", "Ibraheem Adeniran", "Carina Kehrt", "Ingmar Seitz", "Maria Stolz" ], "first_author": "Teemu Joonas Lieb", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Drone", "Climate change", "Aviation", "Environmental impact assessment" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icns69853.2026.11570447" }, { "id": "https://openalex.org/W4411159766", "doi": "10.32604/cmc.2025.063703", "title": "An Improved Multi-Actor Hybrid Attention Critic Algorithm for Cooperative Navigation in Urban Low-Altitude Logistics Environments", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": "en", "authors": [ "Chao Li", "Quanzhi Feng", "Caichang Ding", "Zhiwei Ỹe" ], "first_author": "Chao Li", "venue": "Computers, materials & continua/Computers, materials & continua (Print)", "publisher": null, "abstract": "The increasing adoption of unmanned aerial vehicles (UAVs) in urban low-altitude logistics systems, particularly for time-sensitive applications like parcel delivery and supply distribution, necessitates sophisticated coordin... | Find, read and cite all the research you need on Tech Science Press", "keywords": [ "Computer science", "Low altitude", "Altitude (triangle)", "Environmental science", "Aerospace engineering", "Artificial intelligence", "Engineering", "Mathematics" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://cdn.techscience.press/files/cmc/2025/TSP_CMC-84-2/TSP_CMC_63703/TSP_CMC_63703.pdf" }, { "id": "https://openalex.org/W7212381609", "doi": "10.1016/j.tre.2026.105221", "title": "The relevance of traditional postal services in a diversifying last-mile delivery landscape: The role of human to human (H2H) interactions", "year": 2026, "publication_date": "2026-09-12", "type": "article", "language": "en", "authors": [ "Rico Merkert", "S. Hess", "F. Khan", "M.C.J. Bliemer" ], "first_author": "Rico Merkert", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": "Last-mile delivery research increasingly focuses on business-to-consumer (B2C) automation to satisfy consumers with an ‘I want it now’ mentality, reduce firms’ carbon footprints, and improve cost efficiency. Much less attention has been given to the possibility that there might be differences across consumer segments in their preferences for technology‑enabled or more traditional, human-mediated delivery modes. Building on random utility theory, we developed a hybrid choice model with a latent class kernel and applied it to stated choice data on delivery service preferences collected from 1,007 customers across metropolitan and regional areas of Australia. Our results reveal two latent classes of consumers with distinctly different preferences. The largest group, which we label techies , value speed and low cost last-mile delivery and prefer traditional postal services, followed by aerial drones and parcel lockers, with the effect moderated by parcel value and the availability of a safe place for unattended delivery. The second group, relational, trusting people , place a stronger emphasis on trust and interpersonal aspects of service and substantially prefer traditional postal services (assuming a safe place for delivery is available) and lockers while showing a strong dislike of aerial drones. To interpret these patterns, we draw on social exchange theory and the human-to-human (H2H) relationship model to explain how relational considerations may influence delivery mode preferences. H2H interactions matter for a subset of consumers. Importantly, our broader findings highlight the continued relevance of traditional postal services in a diversifying delivery landscape. Although no direct spatial effect emerges in the class allocation model, our results suggest that residential location (metropolitan versus regional) has a structural effect by influencing consumers’ underlying latent attitudes.", "keywords": [ "Relevance (law)", "Human services", "Human resource management", "Production (economics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S1366554526005594/pdf" }, { "id": "https://openalex.org/W3156851382", "doi": "10.1016/j.ifacol.2020.12.2025", "title": "Measuring Urban Sidewalk Practicability: a Sidewalk Robot Feasibility Index", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Matteo Corno", "Sergio M. Savaresi" ], "first_author": "Matteo Corno", "venue": "IFAC-PapersOnLine", "publisher": "Elsevier BV", "abstract": "Autonomous parcel delivery is attracting a lot of interest. Terrestrial delivery drones travel at lower speeds, are smaller and lighter than passenger cars. These features make them an ideal and valuable first step and experimental sandbox toward fully autonomous vehicles. To be useful, however, small wheeled drones need to operate on parts of the roads that are reserved to pedestrians. This is a challenge by itself. Pedestrian areas are less structured than road and abide by looser rules. The best route for a delivery drone may not be the shortest path; other aspects need to be accounted for that make a route more or less practical for the specific features of the vehicle. This paper introduces a quantitative analysis of these specific issues. The paper proposes a quantitative index that asses a route practicability for a small terrestrial drone. It combines different aspects that account for sidewalk width, sidewalk surface condition, route length and the number of driveways and crosswalks present on the way. We provide the mathematical definition of the index, and use our wheeled drone prototype to show how it can be used to classify and chose the best routes among a selection. Although the index is designed for autonomous drones, given the specific dynamic features of the drone, it can also be employed as is to quantify the accessibility of different routes for disabled people.", "keywords": [ "Drone", "Computer science", "Sandbox (software development)", "Index (typography)", "Pedestrian", "Transport engineering", "Simulation", "Engineering", "World Wide Web" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ifacol.2020.12.2025" }, { "id": "https://openalex.org/W7204824369", "doi": "10.1016/j.tbs.2026.101387", "title": "From awareness to adoption: modeling consumer readiness for urban drone delivery from a stage-change perspective", "year": 2026, "publication_date": "2026-08-31", "type": "article", "language": "en", "authors": [ "Jingcai Yu", "Shunchao Wang" ], "first_author": "Jingcai Yu", "venue": "Travel Behaviour and Society", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Risk perception", "Transtheoretical model", "Technology acceptance model", "Drone", "Theory of reasoned action", "Perspective (graphical)", "Theory of planned behavior", "Social cognitive theory", "Structural equation modeling", "Perception" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2214367X26001560/pdf" }, { "id": "https://openalex.org/W4416008996", "doi": "10.1117/12.3089384", "title": "Efficient last-mile delivery in smart cities: a Q-learning enhanced memetic algorithm for single-vehicle multidrones coordination", "year": 2025, "publication_date": "2025-11-07", "type": "conference-paper", "language": null, "authors": [ "Hanhai Shou", "Jing Zhou", "Yufan Fu", "Zheng Cao", "Yi Jin" ], "first_author": "Hanhai Shou", "venue": null, "publisher": null, "abstract": "With the accelerated construction of smart cities, the intelligent upgrading of logistics systems has emerged as a key breakthrough in addressing the \"last-mile delivery\" challenge. The air-ground collaborative logistics delivery model— integrating ground vehicles and aerial drones—has been demonstrated to outperform single-mode solutions in both efficiency and cost. A typical problem in this context is the synchronous single-vehicle multiple-drones (SVMD) problem. For large-scale scenarios, SVMD has the advantage of being able to coordinate multiple drones to achieve more flexible and efficient logistics distribution, which is of high research value. In this paper, we propose an enhanced memetic algorithm with Q-learning-driven adaptive neighborhood strategy selection to solve the synchronous SVMD problem that integrates path planning and task assignment. We designed different neighborhood operators in the algorithm to enable autonomous training of individuals via a Q-learning mechanism, which allows the algorithm to select the most appropriate search operators for local search. Experimental results suggest that the proposed algorithm achieves higher solution quality while maintaining time efficiency, thus demonstrating its effectiveness in solving the synchronous SVMD problem.", "keywords": [ "Memetic algorithm", "Key (lock)", "Drone", "Context (archaeology)", "Task (project management)", "Selection (genetic algorithm)", "Path (computing)", "Memetics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1117/12.3089384" }, { "id": "https://openalex.org/W7164710901", "doi": null, "title": "Implementing Unmanned Aerial Vehicle (UAV) delivery system in the courier services industry: a systematic review and research trends", "year": 2024, "publication_date": "2024-01-01", "type": "review", "language": "en", "authors": [ "Nik Nur Zaheerah Abdul Rahman", "Wan Marhaini Wan Omar", "Syerina Azlin Md Nasir" ], "first_author": "Nik Nur Zaheerah Abdul Rahman", "venue": "UiTM Institutional Repositories (Universiti Teknologi MARA)", "publisher": "Universiti Teknologi MARA", "abstract": "Unmanned aerial vehicles, or drones, are becoming increasingly popular and are impacting package delivery services by presenting both opportunities and challenges. This research aims to explore the potential of UAVs for last-mile deliveries, their capability to reach remote locations, and the new business opportunities they can generate, particularly in the courier services industry. To gain a competitive edge, courier service companies in emerging markets need to be proactive in understanding the key factors contributing to the acceptance of last-mile UAV delivery services. Hence, the goal of this study is to review the existing literature related to UAV implementation in the courier services industry. A systematic review was employed to gain insight and evaluate the literature. The PRISMA review method was utilized to classify the articles obtained from two reputable bibliographic databases, Web of Science and Scopus, resulting in a limited dataset of 64articles published between 2014 and 2024. The findings revealed that numerous articles were found in the Webof Science database, with the highest number of publications coming from the USA and China. Additionally, most of the articles have been published in International Transactions in Operational Research and Transportation Research Part E: Logistics and Transportation Review. Furthermore, a substantial number of publications are from the business and economics research domain. The study also highlights several research directions to enhance UAV delivery in the courier service industry in the future.", "keywords": [ "Service delivery framework", "Service (business)", "Systematic review", "Key (lock)", "Delivery system", "Web of science", "Information system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ir.uitm.edu.my/view/publication/Conference_e-Proceedings_International_Conference_on_Business_and_Social_Sustainability_=28ICOBSS2024=29.html>," }, { "id": "https://openalex.org/W4405037343", "doi": "10.17825/klr.2024.34.5.65", "title": "A Discussion of the Demand Technology Through Last-Mile Business Data Analysis : ESG, Domestics Courier Value Chain Aspects", "year": 2024, "publication_date": "2024-10-31", "type": "article", "language": "en", "authors": [ "Byung-mo Coo" ], "first_author": "Byung-mo Coo", "venue": "한국물류학회지", "publisher": null, "abstract": "In the Road-map, which made ESG information disclosure mandatory announced by the Korean government in January 2021, environmental and social information will be applied to KOSPI-listed companies with assets of 2 trillion won or more from 2026 and expanded to all KOSPI-listed companies by 2030. This paper analyzed the courier industry, which is a representative industry in the Last-mile service market that constitutes the closest relationship with ESG, by PESTLE methodology. As a result of the analysis, in terms of P/L, four technologies were derived: the development of the daily logistics service industry, the increase in the number of delivery vehicles, how to permit the freight transport business for delivery, and the day on which delivery is off. In terms of E/S, the ratio of single-person households, the number of single-person households, and dual-income couples. In terms of domestic technology of T, the smart logistics center certification system, the delivery HUB terminal-centered AMR, and AGV technology. In terms of global technology, four technologies, including Algoriths and analytics, Delivery drone, Delivery robot, Driverless/Autonomous cars, and O2O sharing economy business model, a special law on the improvement of the air environment in the air management area, and a half-price delivery of convenience stores were derived from the E side. The derived issues and required technology were divided into the hardware part, the parcel supply chain, and the software part, the ESG part, and the implications for ESG’s EㆍSㆍG were presented together with the picture.", "keywords": [ "Last mile (transportation)", "Mile", "Business", "Value (mathematics)", "Computer science", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.17825/klr.2024.34.5.65" }, { "id": "https://openalex.org/W1985440819", "doi": "10.1117/12.719634", "title": "High-speed communications enabling real-time video for battlefield commanders using tracked FSO", "year": 2007, "publication_date": "2007-04-27", "type": "conference-paper", "language": "en", "authors": [ "Mouhammad AlAkkoumi", "Robert C. Huck", "James J. Sluss" ], "first_author": "Mouhammad AlAkkoumi", "venue": "Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE", "publisher": "SPIE", "abstract": "Free Space Optics (FSO) technology is currently in use to solve the last-mile problem in telecommunication systems by offering higher bandwidth than wired or wireless connections when optical fiber is not available. Incorporating mobility into FSO technology can contribute to growth in its utility. Tracking and alignment are two big challenges for mobile FSO communications. In this paper, we present a theoretical approach for mobile FSO networks between Unmanned Aerial Vehicles (UAVs), manned aerial vehicles, and ground vehicles. We introduce tracking algorithms for achieving Line of Sight (LOS) connectivity and present analytical results. Two scenarios are studied in this paper: 1 - An unmanned aerial surveillance vehicle, the Global Hawk, with a stationary ground vehicle, an M1 Abrams Main Battle Tank, and 2 - a manned aerial surveillance vehicle, the E-3A Airborne Warning and Control System (AWACS), with an unmanned combat aerial vehicle, the Joint Unmanned Combat Air System (J-UCAS). After initial vehicle locations have been coordinated, the tracking algorithm will steer the gimbals to maintain connectivity between the two vehicles and allow high-speed communications to occur. Using this algorithm, data, voice, and video can be sent via the FSO connection from one vehicle to the other vehicle.", "keywords": [ "Computer science", "Vehicle tracking system", "Gimbal", "Real-time computing", "Wireless", "Drone", "Battlefield", "Bandwidth (computing)", "Mobile telephony", "Global Positioning System", "Communications system", "Telecommunications" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1117/12.719634" }, { "id": "https://openalex.org/W2952819155", "doi": "10.1109/icstw.2019.00043", "title": "Suggestion of Testing Method for Industrial Level Cyber-Physical System in Complex Environment", "year": 2019, "publication_date": "2019-04-01", "type": "conference-paper", "language": "en", "authors": [ "Jiseob Kim", "Sunil Chon", "Jihwan Park" ], "first_author": "Jiseob Kim", "venue": null, "publisher": null, "abstract": "In this paper, we suggest the testing method for industrial level cyber-physical system and its automation under the various environmental, restrictive condition. There are other testing methods, such as Software in the Loop Test, Hardware in the Loop Test, Field Test. But these methods have limitations of high cost, not enough testing and hard to test because the complexity of the situation is going up. The systems that work near human, like drones, autonomous cars, or used in extreme environments should be tested under same extreme environments and proof that it is safe. And the area in which those systems are used is increasing. For example, the drone is used in the various area not only for leisure but also for broadcasting, surveillance on fire, and parcel delivery. It means the test with a combination of various environment and condition is required to the system. We report the case that we have tested and automated the test with the simulation. With the simulation, we tested the system under the extreme environment, a variety of combination of legal restrictions and situational condition.", "keywords": [ "Cyber-physical system", "Computer science", "Drone", "Automation", "Test (biology)", "Scenario testing", "Field (mathematics)", "System under test", "Test case", "System testing", "Reliability engineering", "Variety (cybernetics)" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icstw.2019.00043" }, { "id": "https://openalex.org/W7203899743", "doi": "10.1016/j.cie.2026.112314", "title": "Hybrid Parcel Delivery Networks: A multi-courier, multi-tier model with UAV integration", "year": 2026, "publication_date": "2026-08-21", "type": "article", "language": "en", "authors": [ "Gabriella Colajanni", "Patrizia Daniele" ], "first_author": "Gabriella Colajanni", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "System integration" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2026.112314" }, { "id": "https://openalex.org/W2095346791", "doi": "10.1117/12.604485", "title": "Mitigation of scintillation noise by common mode rejection", "year": 2005, "publication_date": "2005-05-25", "type": "conference-paper", "language": "en", "authors": [ "Kenneth J. Grant", "Kerry A. Corbett", "Bradley A. Clare", "J. Davies", "Brett Nener" ], "first_author": "Kenneth J. Grant", "venue": "Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE", "publisher": "SPIE", "abstract": "There is increasing interest in free space optical communications as an alternative to fibre optics and radio frequency communications, particularly in 'last mile' applications and applications with weight and power restrictions e.g. communications with unmanned aerial vehicles. The potential advantages of free space optical communications include: high bandwidth; no licensing issues; smaller, lighter payloads; low probability of intercept; and immunity from interference/jamming. However, propagation through the atmosphere is subject to atmospheric scintillation noise affecting the signal-to-noise ratio (SNR), effectively reducing the range and bandwidth of the communication link. This scintillation is experienced even over relatively short propagation paths and is caused by small temperature variations in the atmosphere, resulting in index of refraction changes. In this paper we present a technique to correct for atmospheric scintillation noise in free space optical communications and laser remote sensing. It uses common mode rejection to remove co-channel noise, where each channel is transmitted on separate, but closely spaced, wavelengths. The signal-to-noise ratio is significantly increased, thereby increasing the range and/or bandwidth of the link. To date, tests have been conducted with analogue audio and video transmissions. This has been successful, with improvements of up to 12dB in SNR having been demonstrated. This has been limited by the current implementation, which is only at prototype stage -- the ultimate achievable improvement in SNR is anticipated to be significantly higher.", "keywords": [ "Scintillation", "Free-space optical communication", "Bandwidth (computing)", "Optical communication", "Atmospheric noise", "Computer science", "Noise (video)", "Communications system", "Electrical engineering", "Electronic engineering", "Telecommunications", "Optics" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1117/12.604485" }, { "id": "https://openalex.org/W7163521551", "doi": "10.1016/j.jretconser.2026.104902", "title": "Consumer acceptance of drone delivery services in China’s low-altitude economy: A comparative analysis of two delivery modes", "year": 2026, "publication_date": "2026-06-04", "type": "article", "language": "en", "authors": [ "Zhuangzhuang Wu", "Yuxin Guo", "Jaehoon Lim" ], "first_author": "Zhuangzhuang Wu", "venue": "Journal of Retailing and Consumer Services", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Key (lock)", "Delivery system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jretconser.2026.104902" }, { "id": "https://openalex.org/W4385588096", "doi": "10.1007/978-3-030-97940-9_126", "title": "Energy-Smart Transportation Systems", "year": 2023, "publication_date": "2023-01-01", "type": "book-chapter", "language": "en", "authors": [ "Saba Sabet", "Bilal Farooq" ], "first_author": "Saba Sabet", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Electrification", "Transport engineering", "Sustainable transport", "Greenhouse gas", "Environmental economics", "Engineering", "Business", "Sustainability", "Electricity", "Economics" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-97940-9_126" }, { "id": "https://openalex.org/W4399169397", "doi": "10.1109/wf-iot58464.2023.10539595", "title": "A Mobility-aware Flying Edge Computing Service Orchestration with Quality of Service Support", "year": 2023, "publication_date": "2023-10-12", "type": "conference-paper", "language": "en", "authors": [ "Hugo Santos", "Iago Medeiros", "Carlos Alberto Machado da Rocha", "Denis Lima do Rosário", "Eduardo Cerqueira", "Torsten Ingo Braun" ], "first_author": "Hugo Santos", "venue": null, "publisher": null, "abstract": "Unmanned Aerial Vehicles (UAVs) will be part of last-mile 5G/6G networks and will support Internet of Things (IoT) and low latency services in Flying Edge Computing (FEC). UAVs will densely populate aerial space in smart cities, providing networking and computing to interactive and monitoring services to ground users. FEC is composed of one or a set of UAVs, can cover large areas, and assure the quick deployment of services in 5G/6G systems. FEC will cooperate or even replace edge computing services on the ground network in case of congestion/failure events. However, the efficient selection and orchestration of UAVs to provide Quality of Service (QoS) to mobile users on the ground space is still challenging. This paper proposes a mobility-aware FEC orchestration scheme, called FLYED. FLYED enables UAVs to provide FEC with mobility and QoS support on ground space. Simulation results show the impact and benefits of FLYED in providing QoS assurance compared to state-of-the-art algorithms.", "keywords": [ "Computer science", "Quality of service", "Edge computing", "Orchestration", "Computer network", "Software deployment", "Enhanced Data Rates for GSM Evolution", "Service (business)", "Distributed computing", "Telecommunications", "Operating system" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.1109/wf-iot58464.2023.10539595" }, { "id": "https://openalex.org/W4408006368", "doi": "10.21203/rs.3.rs-6086101/v1", "title": "AI-Driven Digital Transformation and Sustainable Logistics: Innovations in Global Supply Chain Management", "year": 2025, "publication_date": "2025-02-27", "type": "preprint", "language": "en", "authors": [ "Ghazaleh Kermani Moghaddam", "Mostafa Karimzadeh" ], "first_author": "Ghazaleh Kermani Moghaddam", "venue": "Research Square", "publisher": null, "abstract": null, "keywords": [ "Digital transformation", "Business", "Supply chain", "Supply chain management", "Transformation (genetics)", "Industrial organization", "Process management", "Manufacturing engineering", "Computer science", "Engineering", "Marketing", "Chemistry" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.21203/rs.3.rs-6086101/v1" }, { "id": "https://openalex.org/W7154383691", "doi": "10.48321/d1ca963687", "title": "An Efficient Algorithm for Solving Collaborative Truck-Drone Parcel Delivery System Considering En-Route Launching and Recovery Points.", "year": 2026, "publication_date": "2026-01-01", "type": "other", "language": "en", "authors": [ "Maged M. Dessouky" ], "first_author": "Maged M. Dessouky", "venue": "California Digital Library", "publisher": "California Digital Library", "abstract": "The logistics industry faces significant challenges in keeping up with evolving demand and supply conditions, especially in urban areas. Traffic congestion during peak hours makes on-time delivery hard. Moreover, time-sensitive products, such as emergency blood and medicine, must be delivered to the customer at the desired time. Drones are a viable solution to urban logistics problems, as they offer several benefits for package delivery. Drones are resilient to traffic delays since they function independently of road infrastructure, unlike conventional vehicles. However, drones have capacity and other constraints; therefore, collaborating with a drone and a truck can make the delivery system more efficient. Although there has been significant research interest in developing truck-drone routing algorithms, a gap remains in developing models that allow for en-route drone launching points and recovery points. The prior research on truck-drone routing assumes that the truck can only reconnect with a drone at a customer location. In this proposed research, we will expand on the prior work to develop optimization models and algorithms to allow with enroute meet points. This added dimension has the potential to reduce truck vehicle miles and subsequently congestion. Our solution framework will employ a dynamic programming-based algorithm for the initial solution and a synchronized drone dispatch algorithm to determine the launching and recovery points along the truck route. The proposed algorithm will be able to provide solutions for real-world large instances.", "keywords": [ "Drone", "Truck", "Routing (electronic design automation)", "Traffic congestion", "Vehicle routing problem", "Work (physics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.48321/d1ca963687" }, { "id": "https://openalex.org/W4403449968", "doi": "10.3390/su16208949", "title": "Spatial Analysis of Middle-Mile Transport for Advanced Air Mobility: A Case Study of Rural North Dakota", "year": 2024, "publication_date": "2024-10-16", "type": "article", "language": "en", "authors": [ "Raj Bridgelall" ], "first_author": "Raj Bridgelall", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using the mostly rural and small urban U.S. state of North Dakota as a case study. The analysis utilized geographic information system (GIS) and spatial optimization models to strategically assign underutilized airports as multimodal freight hubs to facilitate the shift from long-haul trucks to middle-mile air transport. Key findings demonstrate that electronics, because of their high value-to-weight ratio, are ideally suited for air transport. Comparative analysis shows that transport by drones can reduce the average cost per ton by up to 60% compared to traditional trucking. Optimization results indicate that a small number of strategically placed logistical hubs can reduce average travel distances by more than 13% for last-mile deliveries. Cost analyses demonstrate the viability of drones for middle-mile transport, especially on lower-volume rural routes, highlighting their efficiency and flexibility. The study emphasizes the importance of utilizing existing infrastructure to optimize the logistics network. By replacing truck traffic with drones, AAM can mitigate road congestion, reduce emissions, and extend infrastructure lifespan. These insights have critical implications for supply chain managers, shippers, urban planners, and policymakers, providing a decision support system and a roadmap for integrating AAM into logistics strategies.", "keywords": [ "Mile", "Last mile (transportation)", "Geography", "Environmental science", "Geodesy" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/16/20/8949/pdf?version=1729066657" }, { "id": "https://openalex.org/W4409662020", "doi": "10.4018/979-8-3693-8532-6.ch016", "title": "Drone Integration in Vehicle Routing", "year": 2025, "publication_date": "2025-04-22", "type": "book-chapter", "language": "en", "authors": [ "Tejinder Singh Lakhwani", "Anuj Pal Kapoor", "Yerasani Sinjana" ], "first_author": "Tejinder Singh Lakhwani", "venue": "Advances in environmental engineering and green technologies book series", "publisher": "IGI Global", "abstract": "This chapter examines the integration of drones into Vehicle Routing Problems (VRPs) and their impact on e-commerce and urban logistics. It highlights the benefits of drone delivery, focusing on last-mile logistics, with advantages such as reduced delivery times, cost-effectiveness, and expanded regional coverage. Drones also support environmental sustainability by lowering carbon emissions and promoting energy-efficient operations, aligning with ecological goals. The chapter reviews advancements in technology, optimization models, and routing techniques that enhance drone utility in congested urban areas. However, successful adoption faces challenges, including technical issues, security risks, public acceptance, and legal constraints. By analyzing these limitations, the chapter provides an overview of the current state of drone delivery in VRPs and offers practical recommendations to address these barriers, enabling improved integration of drones into urban logistics while advancing sustainability and reducing environmental impacts.", "keywords": [ "Drone", "Computer science", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.4018/979-8-3693-8532-6.ch016" }, { "id": "https://openalex.org/W4394617363", "doi": "10.4271/2024-01-2882", "title": "Internet of Autonomous Vehicles for The Distribution System of Smart Cities", "year": 2024, "publication_date": "2024-04-08", "type": "conference-paper", "language": "en", "authors": [ "Shizi Ma", "Sheng Wang", "Zhitao Ma", "Zhiguo QI" ], "first_author": "Shizi Ma", "venue": "SAE technical papers on CD-ROM/SAE technical paper series", "publisher": null, "abstract": "With the development of internet technology and autonomous vehicles (AVs), the multimodal transportation and distribution model based on AVs will be a typical application paradigm in the smart city scenario. Before AVs carry out logistics distribution, it is necessary to plan a reasonable distribution path based on each customer point, and this is also known as Vehicle Routing Problem (VRP). Unlike traditional VRP, the urban logistics distribution process based on multimodal transportation mode will use a set of different types of AVs, mainly including autonomous ground vehicles and unmanned aerial vehicles (UAVs). It is worth pointing out that there is currently no research on combining the planning of AVs distribution paths with the trajectory planning of UAVs. To address this issue, this article establishes a bilevel programming model. The upper-level model aims to plan the optimal delivery plan for AVs, while the lower-level model aims to plan a driving trajectory for UAVs. Furthermore, this paper proposes an improved heuristic algorithm for the bilevel programming model. Due to the tendency of Group Search Optimizer (GSO) algorithm to fall into local optima during the process of solving large-scale complex problems, this paper designs an improved GSO algorithm based on improved strategies such as spiral search strategy. During the solving process, based on the upper-level model and using the IGSO algorithm, the distribution order of AVs can be directly solved. In the process of trajectory planning based on the lower-level model, the RRT algorithm is first used to plan an initial trajectory for the UAV. Furthermore, the IGSO algorithm is used to further optimize this trajectory, ultimately achieving the delivery task of the UAV. Finally, a simulation experiment was conducted to compare the effectiveness of the proposed scheme with other algorithms.", "keywords": [ "The Internet", "Computer science", "Distribution (mathematics)", "Internet of Things", "Telecommunications", "Computer security", "World Wide Web" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.4271/2024-01-2882" }, { "id": "https://openalex.org/W2903252716", "doi": "10.9716/kits.2016.15.4.025", "title": "A Study on Utilization of Drone for Public Sector by Analysis of Drone Industry", "year": 2016, "publication_date": "2016-12-31", "type": "article", "language": "en", "authors": [ "Seungbae Sim", "Hun-Yeong Kwon", "Hosang Jung" ], "first_author": "Seungbae Sim", "venue": "Journal of the Korea society of IT services", "publisher": null, "abstract": "The drone is an unmanned aerial vehicle which has no human pilot. Drones can be classified into military drones, commercial drones, and personal drones by usage. Also, drones can be classified from large-sized to nano-sized drone by size and autonomous, remote controlled drone by control type. Especially, military drones can be classified into low-altitude drones, medium-altitude, and high-altitude drones by altitude. Recently, the drone industry is one of the fast growing industries in the world. As drone technologies have become more advanced and cost-effective, Korean government has set its goal to become a top-level country in drone business. However, the government's strict regulation for drone operations is one of the biggest hurdles for the development of the related technologies in Korea and other countries. For example, critical problems for drone delivery can be classified into technical issues and institutional issues. Technical issues include durability, conditional awareness, grasp and release mechanisms, collision avoidance systems, drone operating system. Institutional issues include pilot and operator licensing, privacy rules, noise guidelines, security rules, education for drone police. This study analyzes the trends of the drone industry from the viewpoint of technology and regulation. Also, we define the business areas of drone utilization. Especially, the drone business types or models for public sector are proposed. Drone services or functions promoting public interests need to be aligned with the business reference model of Korean government. To define ten types of drone uses for public sector, we combine the business types of government with the future uses of drones that are proposed by futurists and business analysts. Future uses of drones can be divided into three sectors or services. First, drone services for public or military sectors include early warning systems, emergency services, news reporting, police drones, library drones, healthcare drones, travel drones. Second, drone services for commercial or industrial services include parcel delivery drones, gaming drones, sporting drones, farming and agriculture drones, ranching drones, robotic arm drones. Third, drone services for household sector include smart home drones.", "keywords": [ "Drone", "Government (linguistics)", "Business", "Computer security", "Computer science" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://koreascience.or.kr:80/article/JAKO201609633504636.pdf" }, { "id": "https://openalex.org/W2954842565", "doi": null, "title": "Friendly robot delivery: Designing an autonomous delivery droid for collaborative consumption", "year": 2019, "publication_date": "2019-01-01", "type": "dissertation", "language": "en", "authors": [ "Elin Janebäck", "Matilda Kristiansson" ], "first_author": "Elin Janebäck", "venue": null, "publisher": null, "abstract": "Abstract \nHUGO is an autonomous, last mile delivery robot concept currently under development\nby Gothenburg based tech agency Berge. The aim of this thesis was to design a top module\nfor HUGO, making the robot fit into the context of collaborative consumption. \n\nA literature study about collaborative consumption, last mile delivery, and robot interaction\nwas conducted to deepen the understanding of these subjects and to find requirements\nthat the context of collaborative consumption pose on HUGO. Also, potential HUGO\nusers were repeatedly involved throughout the project to establish user needs and requirements\nposed on the robot in order to make it visually appealing and user friendly. To\ngather user insights, a questionnaire was sent out, interviews were held and focus groups\nwere implemented. User needs and criteria were identified regarding the design and function\nof the robot as well as the delivery service connected to it. \n\nA brief attempt at integrating a delivery robot into current Swedish collaborative consumption\nservices was made by creating user journeys showing step by step how the\nservice could work. \n\nSome concerns emerged regarding the integration of autonomous delivery robots in the\npublic space, however, the user study indicated that users are generally positive to autonomous\ndelivery drones, proving HUGO’s potential as delivery method. The user study\nfurther indicated that for an autonomous delivery robot to be accepted in the public space,\nit is essential that its purpose and primary function are obvious. \n\nThe project resulted in HUGO C - a product proposal for a delivery robot suitable for\ncollaborative consumption. This concept is unique in that it is modular and can transport\nbetween one and four parcels at a time as well as adapt its compartment sizes to the user\nneeds.", "keywords": [ "Context (archaeology)", "Robot", "Planner", "Service (business)", "Service delivery framework", "Consumption (sociology)", "Human–computer interaction", "Computer science", "Engineering", "Multimedia", "Artificial intelligence", "Business" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "http://publications.lib.chalmers.se/records/fulltext/257174/257174.pdf" }, { "id": "https://openalex.org/W7160402778", "doi": "10.5281/zenodo.20047074", "title": "DRONE-BASED DELIVERY IN LOGISTICS", "year": 2026, "publication_date": "2026-05-06", "type": "dataset", "language": "en", "authors": [ "Shodmonov Sayidbek Abduvayitovich" ], "first_author": "Shodmonov Sayidbek Abduvayitovich", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "This systematic review synthesizes peer-reviewed and policy literature (2025–2026) on drone-based last-mile delivery, emphasizing economic viability, life-cycle environmental impacts, and regulatory constraints. A structured search across Scopus, Web of Science, ScienceDirect and selected policy portals yielded 32 studies for in-depth analysis. Results show that unmanned aerial vehicles (UAVs) provide meaningful operational advantages — notably delivery speed and reach for lightweight and urgent shipments — while environmental benefits are conditional on operational context and energy sources. Techno-economic studies indicate drones are financially attractive in niche applications (medical, emergency, remote delivery), but high capital expenditures, infrastructure needs, and regulatory fragmentation limit scale-up. The review concludes with concrete policy and business recommendations and highlights priority research directions, including integrated LCA–TEA–network modeling and large-scale real-world pilots.", "keywords": [ "Context (archaeology)", "Drone", "Fragmentation (computing)", "Capital (architecture)", "Business model", "Public policy", "Environmental policy", "Best practice" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20047074" }, { "id": "https://openalex.org/W7160241290", "doi": "10.5281/zenodo.20038673", "title": "DRONE-BASED DELIVERY IN LOGISTICS", "year": 2026, "publication_date": "2026-05-05", "type": "dataset", "language": "en", "authors": [ "Shodmonov Sayidbek Abduvayitovich" ], "first_author": "Shodmonov Sayidbek Abduvayitovich", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "This systematic review synthesizes peer-reviewed and policy literature (2025–2026) on drone-based last-mile delivery, emphasizing economic viability, life-cycle environmental impacts, and regulatory constraints. A structured search across Scopus, Web of Science, ScienceDirect and selected policy portals yielded 32 studies for in-depth analysis. Results show that unmanned aerial vehicles (UAVs) provide meaningful operational advantages — notably delivery speed and reach for lightweight and urgent shipments — while environmental benefits are conditional on operational context and energy sources. Techno-economic studies indicate drones are financially attractive in niche applications (medical, emergency, remote delivery), but high capital expenditures, infrastructure needs, and regulatory fragmentation limit scale-up. The review concludes with concrete policy and business recommendations and highlights priority research directions, including integrated LCA–TEA–network modeling and large-scale real-world pilots.", "keywords": [ "Context (archaeology)", "Drone", "Fragmentation (computing)", "Capital (architecture)", "Business model", "Public policy", "Environmental policy", "Best practice" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20038673" }, { "id": "https://openalex.org/W7160267836", "doi": "10.5281/zenodo.20038672", "title": "DRONE-BASED DELIVERY IN LOGISTICS", "year": 2026, "publication_date": "2026-05-05", "type": "dataset", "language": "en", "authors": [ "Shodmonov Sayidbek Abduvayitovich" ], "first_author": "Shodmonov Sayidbek Abduvayitovich", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "This systematic review synthesizes peer-reviewed and policy literature (2025–2026) on drone-based last-mile delivery, emphasizing economic viability, life-cycle environmental impacts, and regulatory constraints. A structured search across Scopus, Web of Science, ScienceDirect and selected policy portals yielded 32 studies for in-depth analysis. Results show that unmanned aerial vehicles (UAVs) provide meaningful operational advantages — notably delivery speed and reach for lightweight and urgent shipments — while environmental benefits are conditional on operational context and energy sources. Techno-economic studies indicate drones are financially attractive in niche applications (medical, emergency, remote delivery), but high capital expenditures, infrastructure needs, and regulatory fragmentation limit scale-up. The review concludes with concrete policy and business recommendations and highlights priority research directions, including integrated LCA–TEA–network modeling and large-scale real-world pilots.", "keywords": [ "Context (archaeology)", "Drone", "Fragmentation (computing)", "Capital (architecture)", "Business model", "Public policy", "Environmental policy", "Best practice" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20038672" }, { "id": "https://openalex.org/W7160426377", "doi": "10.5281/zenodo.20047075", "title": "DRONE-BASED DELIVERY IN LOGISTICS", "year": 2026, "publication_date": "2026-05-06", "type": "dataset", "language": "en", "authors": [ "Shodmonov Sayidbek Abduvayitovich" ], "first_author": "Shodmonov Sayidbek Abduvayitovich", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "This systematic review synthesizes peer-reviewed and policy literature (2025–2026) on drone-based last-mile delivery, emphasizing economic viability, life-cycle environmental impacts, and regulatory constraints. A structured search across Scopus, Web of Science, ScienceDirect and selected policy portals yielded 32 studies for in-depth analysis. Results show that unmanned aerial vehicles (UAVs) provide meaningful operational advantages — notably delivery speed and reach for lightweight and urgent shipments — while environmental benefits are conditional on operational context and energy sources. Techno-economic studies indicate drones are financially attractive in niche applications (medical, emergency, remote delivery), but high capital expenditures, infrastructure needs, and regulatory fragmentation limit scale-up. The review concludes with concrete policy and business recommendations and highlights priority research directions, including integrated LCA–TEA–network modeling and large-scale real-world pilots.", "keywords": [ "Context (archaeology)", "Drone", "Fragmentation (computing)", "Capital (architecture)", "Business model", "Public policy", "Environmental policy", "Best practice" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20047075" }, { "id": "https://openalex.org/W3184384698", "doi": null, "title": "Design of Delivery Drone", "year": 2021, "publication_date": "2021-07-01", "type": "article", "language": "en", "authors": [ "S Mohaneshwar", "Ragipati Karthik", "Rahul Batapagari", "Ninganna Gangappa Bani", "Varun Kumar Reddy N" ], "first_author": "S Mohaneshwar", "venue": "Journal of Emerging Technologies and Innovative Research", "publisher": "Journal of Emerging Technologies and Innovative Research (JETIR)", "abstract": "At present, delivery system should be fast and efficient in various fields like medical, foods, package deliveries etc. Traditional method for delivery is slow and inefficient in last mile delivery. So, introducing drones in last mile delivery makes faster and more efficient. This paper represents Quadcopter as a low weight and low-cost autonomous flight capable of delivering parcel. This quadcopter drone is capability of delivering parcel ordered and coming back to the starting point. The promising result of this method enables future research on using quadcopter for delivering parcel.", "keywords": [ "Quadcopter", "Drone", "Last mile (transportation)", "Mile", "Food delivery", "Computer science", "Point (geometry)", "Aeronautics", "Simulation", "Engineering", "Aerospace engineering", "Business" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.jetir.org/papers/JETIREX06025.pdf" }, { "id": "https://openalex.org/W4390087371", "doi": null, "title": "Time-adapted Early Arrival Path for Drone Parcel Delivery through Public Transportation Vehicles: Using Q-learning", "year": 2023, "publication_date": "2023-02-20", "type": "conference-paper", "language": "en", "authors": [ "Mohammed Rahmani", "Florian Delavernhe", "Sidi‐Mohammed Senouci", "Marion Berbineau" ], "first_author": "Mohammed Rahmani", "venue": "HAL (Le Centre pour la Communication Scientifique Directe)", "publisher": "Centre National de la Recherche Scientifique", "abstract": "International audience", "keywords": [ "Drone", "Path (computing)", "Public transport", "Computer science", "Transport engineering", "Aeronautics", "Real-time computing", "Simulation", "Artificial intelligence", "Engineering", "Computer network" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ube.hal.science/hal-04357344" }, { "id": "https://openalex.org/W7152396760", "doi": "10.70675/b90f39c1z06aez479ez8948z62d4786c3e87", "title": "Solving vehicle routing problems with drones in urban logistics : an approach based on exact and approximate optimization methods", "year": 2026, "publication_date": "2026-02-04", "type": "dissertation", "language": "en", "authors": [ "Sylvain Lichau" ], "first_author": "Sylvain Lichau", "venue": null, "publisher": null, "abstract": "Résolution de problèmes de tournées de véhicules avec drones en logistique urbaine : une approche basée sur les méthodes d’optimisation exactes et approchées Les drones constituent un complément prometteur pour la logistique de livraison. Ils présentent des caractéristiques fondamentalement différentes de celles des véhicules classiques : des coûts d’utilisation plus faibles et des vitesses plus élevées, au détriment d’une autonomie et d’une capacité réduite. Pour les applications où ces contraintes sont acceptables, les drones peuvent remplacer entièrement les véhicules de livraison. Cependant, dans la plupart des cas, il est nécessaire de combiner stratégiquement ces types de véhicules complémentaires afin de tirer le meilleur parti de leurs atouts opérationnels respectifs. Cette thèse propose principalement des méthodes mathématiques d’optimisation exactes pour les problèmes de routage avec drones. Le premier chapitre propose une revue de littérature consacrée aux problèmes de routage avec drones dans le domaine de la recherche opérationnelle, en mettant l’accent sur les méthodes d’optimisation exactes. Nous soulignons la diversité des problèmes abordés par les chercheurs ainsi que la nécessité d’augmenter la taille des instances résolues à l’optimale. Le deuxième chapitre rappelle brièvement les concepts de programmation mathématique nécessaires à la compréhension des algorithmes de «branch-cut-and-price». Nous décrivons également l’algorithme utilisé dans cette thèse, en détaillant ses composantes avancées ainsi que l’algorithme de «labeling» employé pour résoudre les sous-problèmes. Le troisième chapitre traite du «Two-Echelon Vehicle Routing Problem with Drones». Nous proposons un nouveau modèle de partitionnement d’ensembles, dans lequel les chemins partiels correspondant aux mouvements des drones sont énumérés à l’aide d’un programme dynamique. Nous présentons également une adaptation des «rounded capacity cuts», spécialement conçue pour résoudre ce problème. Par ailleurs, nous développons une heuristique basée sur l’algorithme exact. Les expériences numériques montrent que l’algorithme exact augmente considérablement la taille des instances résolues de manière optimale. Pour évaluer le modèle, l’algorithme est ensuite étendu pour traiter le «Park-and-Loop Routing Problem». Le quatrième chapitre traite du «Truck-based Drone Delivery Routing Problem with Time Windows». Nous développons un algorithme exact de branch-cut-and-price ainsi qu’un algorithme de «labeling» pour résoudre le sous-problème. Nous comparons deux modèles de sous-problème alternatifs définis sur des graphes distincts et montrons qu’aucun des deux ne domine l’autre : le meilleur choix dépend des caractéristiques de l’instance considérée. Les expériences numériques démontrent l’efficacité des approches proposées. Nous introduisons également de nouvelles instances plus complexes, où la capacité des drones est augmentée. Le cinquième chapitre étudie une variante du «Vehicle Routing Problem with Time Windows», qui intègre deux caractéristiques pertinentes sur le plan opérationnel : des heures de départ flexibles depuis le dépôt et des limites strictes sur la durée des routes. Bien que plus générique, ce problème peut s’apparenter à un problème de routage de drones dans lequel la portée est limitée par la durée du trajet. Nous développons un algorithme de branch-cut-and-price, dont la composante principale est un algorithme de «labeling» bidirectionnel résolvant le sous-problème. Nous montrons également comment traiter le problème connexe de minimisation de la durée totale du trajet. Les expériences numériques confirment les performances de l’algorithme.", "keywords": [ "Drone", "Vehicle routing problem", "Routing algorithm", "Routing (electronic design automation)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://www.theses.fr/2026BORD0010/document" }, { "id": "https://openalex.org/W4402156972", "doi": "10.2139/ssrn.4931448", "title": "Optimization of Multi-Agent Flying Sidekick Traveling Salesman Problem Over Road Networks", "year": 2024, "publication_date": "2024-01-01", "type": "preprint", "language": "en", "authors": [ "Ruixiao Yang", "Chuchu Fan" ], "first_author": "Ruixiao Yang", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Travelling salesman problem", "Computer science", "Algorithm" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.2139/ssrn.4931448" }, { "id": "https://openalex.org/W7213419340", "doi": "10.1109/bigdia71496.2026.11684637", "title": "A Deep Reinforcement Learning Approach to Collaborative Truck–Drone Routing Optimization for E-commerce Parcel Delivery in Mountainous Terrain", "year": 2026, "publication_date": "2026-08-01", "type": "conference-paper", "language": null, "authors": [ "Yunlian Chi", "Jiawu Peng", "Yaoyu Li" ], "first_author": "Yunlian Chi", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Terrain", "Reinforcement learning", "Routing (electronic design automation)", "Training (meteorology)", "Control (management)", "Raised-relief map" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/bigdia71496.2026.11684637" }, { "id": "https://openalex.org/W4414517646", "doi": "10.63550/iceip.2025.22.11.069", "title": "Implementation of Drones in Logistics System", "year": 2025, "publication_date": "2025-09-11", "type": "conference-paper", "language": "en", "authors": [ "O.R. Gabbasova", "Константин Владимирович Осинцев", "Nikita A. Pshenisnov" ], "first_author": "O.R. Gabbasova", "venue": null, "publisher": null, "abstract": "This article assesses the prospects for the development and change of logistics systems in accordance with the introduction of unmanned drones. Their use is an innovative solution that can significantly improve the efficiency of goods transfer. Key technological parameters, such as the global positioning system (GPS), are considered. Calculations are made to estimate the number of drones required delivering 100,000 orders per day, and various drone models are analyzed. The relevance of using drones in solving warehouse problems and delivering goods on the \"last mile\" is described. Domestic experience in using quadcopters in logistics is touched upon. Particular attention is paid to the scalability of unmanned aerial vehicles for delivery to hard-to-reach areas, such as the Arctic zone of the Russian Federation. The use of drones in urban areas is also taken into account.", "keywords": [ "Drone", "Key (lock)", "Relevance (law)", "Scalability", "Humanitarian Logistics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.63550/iceip.2025.22.11.069" }, { "id": "https://openalex.org/W7172508952", "doi": "10.1007/s40860-026-00274-6", "title": "Drones-dt: dynamic management of drone fleets represented by Digital Twins", "year": 2026, "publication_date": "2026-08-05", "type": "article", "language": "en", "authors": [ "Miqueias Araújo", "Lucas Silva", "Iure Fé", "Jonas Nunes", "Francinaldo Barbosa", "Iago Almeida", "Luiz Bittencourt", "Francisco Airton Silva" ], "first_author": "Miqueias Araújo", "venue": "Journal of Reliable Intelligent Environments", "publisher": "Springer Science+Business Media", "abstract": "Abstract Drone-based delivery systems have emerged as a promising solution for urban logistics, offering fast, flexible last-mile delivery. However, fluctuations in demand for requests over time make fleet sizing challenging. Overprovisioning leads to resource underutilization and higher operational costs, while underprovisioning may lead to delivery delays and violations of Service Level Agreements (SLAs). To address this challenge, this work proposes Drones-DT, a Digital Twin architecture designed for dynamic drone fleet management. The approach relies on a Stochastic Petri Net (SPN) analytical model synchronized with a delivery simulator to maintain a continuously updated Digital Shadow of the system. Based on real-time metrics, the Digital Twin performs predictive what-if analyses to estimate performance indicators, such as Mean Mission Time (MMT), system throughput, fleet utilization, and energy consumption, across different fleet configurations. A SLA-oriented decision mechanism, implemented through a binary search strategy, determines the minimum number of drones required to satisfy the target delivery time. The SPN model was statistically validated against a discrete-event simulator, yielding results equivalent to those of the simulator for MMT and throughput at the 95% confidence level. A case study demonstrates that Drones-DT maintains SLA compliance while operating with a significantly smaller average fleet than static provisioning strategies, achieving up to a 16% reduction in energy consumption and associated CO 2 emissions.", "keywords": [ "Provisioning", "Drone", "Sizing", "Throughput", "Energy consumption", "Service (business)", "Fleet management", "Work (physics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://link.springer.com/content/pdf/10.1007/s40860-026-00274-6.pdf" }, { "id": "https://openalex.org/W7131620160", "doi": "10.2196/preprints.92517", "title": "A Human-Centered Approach to Address “Last Mile” Barriers to Healthcare Access: Co-designing mobile clinics for underserved populations (Preprint)", "year": 2026, "publication_date": "2026-02-17", "type": "preprint", "language": null, "authors": [ "Stephanie Tulk Jesso", "Ann E. Fronczek", "Amy Booth", "Joseph Trombetta", "Mehmet Yildirim", "Negin Esmaeili", "Shiqi Zhang", "Sean Dolan", "Michael DiFabio", "Anemone Kasasbeh", "Kayla Velie", "Sreenath Chalil Madathil", "Christopher Alderman", "Sumantra Sarkar" ], "first_author": "Stephanie Tulk Jesso", "venue": null, "publisher": null, "abstract": "BACKGROUND In the United States, many individuals lack adequate access to healthcare services due to a host of economic, logistical, and social barriers. Telehealth technologies and mobile health clinics present the opportunity to close the “last mile” between patients and healthcare services. OBJECTIVE Our multidisciplinary team from healthcare and academia wanted to design a mobile health clinic with potential telehealth services, along with the supporting infrastructure as a first step towards developing such a program for our region. METHODS Our multidisciplinary team hosted a co-design session to collaboratively design and mock-up mobile health clinic services aimed at serving the needs of our community, with an emphasis on vulnerable populations within our region. RESULTS This session yielded insights into the necessity for flexible space, equipment, and staff, and how “high-tech” tools, like drones and robots, along with a fleet of small, medium, and large mobile health clinics, could be maximally positioned to traverse “the last mile” and provide equitable healthcare to our community. CONCLUSIONS The use of mobile clinics to address last-mile challenges could have a transformative impact on community health, and co-design is a valuable tool to elucidate pragmatic opportunities to target first, and can aid in developing a broader roadmap to scale up strategically and sustainably.", "keywords": [ "Telehealth", "Multidisciplinary approach", "Health care", "Session (web analytics)", "Telemedicine", "Mobile technology", "Scale (ratio)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2196/preprints.92517" }, { "id": "https://openalex.org/W3176444184", "doi": "10.1016/b978-0-08-102671-7.10272-6", "title": "Drones in Freight Transport", "year": 2021, "publication_date": "2021-01-01", "type": "reference-entry", "language": "en", "authors": [ "Oliver Kunze" ], "first_author": "Oliver Kunze", "venue": "Elsevier eBooks", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Aeronautics", "Transport engineering", "Engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/b978-0-08-102671-7.10272-6" }, { "id": "https://openalex.org/W3113273073", "doi": null, "title": "The traveling salesman problem with drone", "year": 2019, "publication_date": "2019-01-01", "type": "dissertation", "language": "en", "authors": [ "Quang Minh Ha" ], "first_author": "Quang Minh Ha", "venue": "Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))", "publisher": "UCLouvain", "abstract": "Over the past few years, unmanned aerial vehicles (UAV), also known as drones, have been adopted as part of a new logistic method in the commercial sector called \"last-mile delivery\". In this novel approach, they are deployed alongside trucks to deliver goods to customers to improve the quality of service and reduce the transportation cost. This approach gives rise to a new variant of the traveling salesman problem (TSP), called TSP with drone (TSP-D). A variant of this prob- lem that aims to minimize the time at which truck and drone finish the service (or, in other words, to maximize the quality of service) was studied in the work of Murray and Chu (2015). In this thesis, we propose two new variants of the TSP-D: the Min- Cost TSP-D and the Multi-Visits TSP-D. With each of this variant, a mathematical model – a MIP formulation – is presented. Further- more, with the development of three metaheuristics (GRASP, HGA, ILS) based on local search, we can solve the problem in both min- time and min-cost objective efficiently under an acceptable time. The computational results show that our proposed methods could outperform the ones in the previous work and could significantly improve the solution quality when comparing to the optimal TSP solution. Furthermore, the extensive analysis of the components of the heuristic as well as the parameters of the variants, we can under- stand more about the algorithm’s sensitivity as well as the nature of the problem.", "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Biology", "Algorithm" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/2078.1/222932" }, { "id": "https://openalex.org/W7201837744", "doi": "10.1504/ijor.2026.155580", "title": "Multiple drone and truck combined operations", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": "en", "authors": [ "Bhawesh Sah", "Mohammad Moshref Javadi", "Sung Hoon Chung" ], "first_author": "Bhawesh Sah", "venue": "International Journal of Operational Research", "publisher": "Inderscience Publishers", "abstract": "Drones, also known as unmanned aerial vehicles (UAVs), have the capability to improve the responsiveness in parcel distribution process, however, drone delivery suffers from shortcomings such as limited battery life, and weight-carrying constraints. These shortcomings can be overcome if a drone works in conjunction with a truck to make parcel deliveries. In contrast to earlier models which focus on one drone and one truck, in this paper, we propose a novel model in which multiple drones and trucks can work together to fulfil the logistics operations, a drone can depart from a truck and return back to the same or a different truck after completing the operations and a truck can house multiple drones. We present a mixed integer linear programming formulation of the problem and present results from several heuristics such as genetic algorithm (GA), simulated annealing (SA), and greedy search combined with the insertion method.", "keywords": [ "Drone", "Truck", "Heuristics", "Integer programming", "Simulated annealing", "Linear programming" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1504/ijor.2026.155580" }, { "id": "https://openalex.org/W4288760153", "doi": "10.1016/j.jss.2022.111456", "title": "EdgeWorkflow: One click to test and deploy your workflow applications to the edge", "year": 2022, "publication_date": "2022-07-30", "type": "article", "language": "en", "authors": [ "Xu Jia", "Ran Ding", "Xiao Liu", "Xuejun Li", "John Grundy", "Yun Jin Yang" ], "first_author": "Xu Jia", "venue": "Journal of Systems and Software", "publisher": "Elsevier BV", "abstract": "In recent years, edge computing has become the ideal computing paradigm for various smart systems, such as smart logistics, smart health and smart transportation. This is due to its advantages including fast response times, energy efficiency and cost effectiveness over conventional cloud computing platforms. However, running complex computational scientific workflow tasks is still a very challenging issue at the edge, due to its typical three-layered computing environment consisting of an end device layer, an edge server layer, and a cloud server layer. A large number of recent studies have proposed different solutions for optimizing such computing resource management problems in an edge computing environment. However, since evaluation of most such studies is conducted through simulation, the effectiveness cannot be guaranteed in a real world environment. Therefore, to advance research on efficient execution and deployment problems for real world workflow applications using edge computing, an open-source edge workflow management system with comprehensive empirical evaluation capabilities is urgently required. This paper presents the first edge workflow system (named EdgeWorkflow) that is able to deploy user-created workflow applications to a real-world edge computing environment with “one-click” after optimizing the configuration with the simulation tool. With the aid of EdgeWorkflow, the user can automate the generation of specific edge computing environments, easily model and generate executable workflow applications with a visual modelling tool, effectively select various resource management methods included in the systems or apply their own resource management and task scheduling algorithms, efficiently monitor the statuses of computational tasks and obtain comprehensive reports on the execution results (such as those regarding time, cost and energy). We use an edge computing-based unmanned aerial vehicle (UAV) last-mile delivery system as a real-world case study, and a number of representative scientific workflows are employed for our experiments. Our experimental results show that EdgeWorkflow can effectively evaluate the performance of different resource management and workflow task scheduling algorithms and efficiently deploy and execute user-defined scientific workflow applications to user-specified edge computing environments.", "keywords": [ "Workflow", "Edge computing", "Computer science", "Cloud computing", "Executable", "Distributed computing", "Workflow management system", "Workflow engine", "Scheduling (production processes)", "Enhanced Data Rates for GSM Evolution", "Workflow technology", "Database" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S0164121222001479/pdf" }, { "id": "https://openalex.org/W4391557250", "doi": null, "title": "Droning on to Delivery: Examining the Energy Impacts of Using Drones for Moving Goods", "year": 2024, "publication_date": "2024-02-05", "type": "article", "language": "en", "authors": [ "Victor Walker" ], "first_author": "Victor Walker", "venue": "OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)", "publisher": "Office of Scientific and Technical Information", "abstract": "The demand for fast, localized delivery has grown significantly in recent years. Whether for cheesy snacks, prepared food, medical solutions, or business deliveries, fast and efficient delivery is increasingly a demand and differentiator. Drone delivery in the freight sector offers to revolutionize last-mile logistics and improve services. This research analyzes the impacts of drone energy for delivery operations, aiming to compare various types of drones (large and small, rotary and VTOL) and various types of business methods. The project executes novel open-air and laboratory-based testing to look at the impacts of weights, operations, temperatures and weather conditions. The study combines this real-world experimental data with fleet optimization mathematical models to assess energy consumption of different scenarios as well as examine the minimum fleet size and additional battery requirements. These fleet optimization models compare energy between types of deployments with existing delivery methods. The model was also extended to look at mixed fleets of aerial drones and ground vehicles to accommodate different restrictions on drones or when weather prohibits their use. The analysis provided insights into factors such as drone design, payload weight, flight distance, weather conditions and operational parameters and impacts of each. It showed how to combine different types of vehicles to reduce energy and improve services. And it showed that drone speed, routing restrictions, and unfavorable weather significantly influence energy consumption. Our open experiment data and optimization models can assist stakeholders and industry in understanding drone package delivery and offers keys to improving deployment.", "keywords": [ "Drone", "Energy (signal processing)", "Computer science", "Business", "Environmental economics", "Economics", "Physics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.osti.gov/servlets/purl/2283555" }, { "id": "https://openalex.org/W4402299041", "doi": "10.17725/j.rensit.2024.16.629", "title": "Enhancing Drone Stability in Adverse Weather Conditions: A Novel MySQL-Based Approach for Balancing UAVs in Rain", "year": 2024, "publication_date": "2024-09-06", "type": "article", "language": "en", "authors": [ "Mohammed Hussein", "Abdullah Qays Taher", "Mohammed Jasim Mohammed", "Alaan Ghazi", "Abdullah Mohammed Awad", "Sharmeen Izzat Hassan", "Haider Mahmood Jawad", "Marwa Saad Mahdi Hussin", "Bektur Abdyrahmanovich Azimov" ], "first_author": "Mohammed Hussein", "venue": "Radioelectronics Nanosystems Information Technologies", "publisher": null, "abstract": "Background: Unmanned Aerial Vehicles (UAVs) can potentially transform several sectors, notably last-mile delivery. Despite its potential, their implementation in real-world situations, particularly in severe weather like rain, must be improved with route optimisation and stability issues. Objective: This study aims to provide a fresh approach to the issues that drones confront in wet weather using unique MySQL code designed to improve drone performance in such environments. Methods: A customised algorithm based on the Vehicle Routing Problem (VRP) was specially adapted for drone delivery. It considers battery life, payload weight, and estimated delivery timeframes. This algorithm aims to alter the drone's path under wet circumstances to maintain balance, preserve energy, and reduce the possibility of delivery failure. Results: Using MySQL custom code for drones may bring several advantages. It may not only increase battery life by guaranteeing appropriate routing, but it may also shorten delivery times and prevent cases of lost or damaged items due to weather. Delivery efficiency may be significantly improved. Conclusion: Incorporating bespoke MySQL code provides a viable option for addressing the inherent issues that drones confront in damp situations. This technology allows for more dependable and effective drone deliveries, even in less-than-ideal weather circumstances, by optimising routes and assuring stability.", "keywords": [ "Drone", "Adverse weather", "Stability (learning theory)", "Weather modification", "Meteorology", "Computer science", "Environmental science", "Aeronautics", "Geography", "Engineering", "Machine learning", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://en.rensit.ru/vypuski/article/594/16(5)629-642e.pdf" }, { "id": "https://openalex.org/W7134818034", "doi": "10.1002/eng2.70676", "title": "Mixed Integer Programming ( MIP ) for UAV Logistics Path Optimization: Charging Station Location and Multi‐Objective Distribution Collaborative Decision‐Making", "year": 2026, "publication_date": "2026-03-01", "type": "article", "language": "en", "authors": [ "Guiquan Jiang" ], "first_author": "Guiquan Jiang", "venue": "Engineering Reports", "publisher": "Wiley", "abstract": "ABSTRACT Large‐scale UAV logistics deployment faces critical challenges from dynamic energy consumption in complex terrains, disconnected optimization of charging infrastructure and route planning, and multi‐objective conflicts. This study proposes a three‐dimensional “energy‐route‐objective” collaborative framework integrating charging station site selection, dynamic routing, and multi‐objective decision‐making via mixed integer programming (MIP). A two‐level optimization model is constructed: the upper level minimizes station construction costs while maximizing service coverage using discrete location variables; the lower level incorporates hyperspectral remote sensing‐derived terrain adaptive coefficients to quantify elevation/electromagnetic impacts on energy consumption, embedding dynamic constraints and time window penalties. A parallel adaptive large neighborhood search (PALNS) algorithm simultaneously optimizes operating costs, delivery timeliness, and demand fairness. Innovations include a Pareto archiving mechanism with dynamic damage‐repair for multi‐objective convergence; electromagnetic‐interference‐aware energy modeling; and spatiotemporal coupling of station utilization with route traffic. Validation across China's Hengduan Mountains and Jining City logistics networks demonstrates 31% reduction in operating costs; charging station utilization standard deviation decreased from 0.37 to 0.15; 93.8% on‐time delivery rate achieved; PALNS attained 0.87 hypervolume in 285 s (17.6% faster than NSGA‐II); and 89.7% routing success rate in complex terrain. The framework resolves resource‐load mismatches by dynamically synchronizing infrastructure planning and routing, while the terrain‐adaptive module enhances robustness in mountainous areas. The multi‐objective weighting function effectively balances timeliness deviation and cost elasticity. This provides a global optimization paradigm for UAV logistics networks with methodological implications for smart city energy scheduling. Future work will integrate weather forecasting and battery degradation models, and explore quantum computing acceleration.", "keywords": [ "Energy consumption", "Integer programming", "Robustness (evolution)", "Multi-objective optimization", "Base station", "Robust optimization", "Dynamic programming", "Sorting" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/eng2.70676" }, { "id": "https://openalex.org/W4406936268", "doi": "10.60143/ijls.v10.i1.2024.125", "title": "Drones and Privacy: The Indian Story", "year": 2024, "publication_date": "2024-12-30", "type": "article", "language": "en", "authors": [ "Abhishek Dua" ], "first_author": "Abhishek Dua", "venue": "International Journal of Law and Social Sciences", "publisher": null, "abstract": "In the 21st century, the industry of drones, also known as Unmanned Aerial Vehicles (UAVs) or Remote Piloted Aircraft Systems (RPAS), has witnessed an exponential growth, more so in civilian applications, such as surveillance and parcel delivery. From its traditional use in military operations for over a century, drones have readily been introduced in various industries ranging from agriculture, media, mining, insurance to mention a few, due to its revolutionary benefits and affordability. However, the use of drone technology has its pitfalls too. Its intricate software and hardware have the ability to use a variety of sensors to gather information/data from unique vantage points-for long periods and on a continuous basis. The prospect of having every move, every action, being monitored and possibly recorded, raises grave privacy concerns. This paper is aimed to offer a brief introduction to the concept of drones, associated privacy risks/concerns, the extant regulatory regime and finally concludes with suggestions and countermeasures to mitigate the risk.", "keywords": [ "Drone", "Internet privacy", "Computer security", "History", "Computer science", "Biology", "Genetics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.journalsalliancepub.com/index.php/ijls/article/download/125/98" }, { "id": "https://openalex.org/W4286850438", "doi": "10.48550/arxiv.2111.13050", "title": "The vehicle routing problem with drones and drone speed selection", "year": 2021, "publication_date": "2021-11-25", "type": "preprint", "language": "en", "authors": [ "Felix Tamke", "Udo Buscher" ], "first_author": "Felix Tamke", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "Joint parcel delivery by trucks and drones has enjoyed significant attention for some time, as the advantages of one delivery method offset the disadvantages of the other. This paper focuses on the vehicle routing problem with drones and drone speed selection (VRPD-DSS), which considers speed-dependent energy consumption and drone-charging in detail. For this purpose, we formulate a comprehensive mixed-integer problem that aims to minimize the operational costs consisting of fuel consumption costs of the trucks, labor costs for the drivers, and energy costs of the drones. The speed at which a drone performs a flight must be selected from a discrete set. We introduce preprocessing steps to eliminate dominated speeds for a flight to reduce the problem size and use valid inequalities to accelerate the solution process. The consideration of speed-dependent energy consumption leads to the fact that it is advisable to perform different flights at different speeds and not to consistently operate a drone at maximum speed. Instead, drone speed should be selected to balance drone range and speed of delivery. Our extensive computational study of a rural real-world setting shows that, by modeling energy consumption realistically, the savings in operational costs compared to truck-only delivery are significant but smaller than those identified in previously published work. Our analysis further reveals that the greatest savings stem from the fact that overall delivery time decreases compared to truck-only delivery, allowing costly truck-driver time to be reduced. The additional energy costs of the drone, however, are largely negligible.", "keywords": [ "Drone", "Truck", "Energy consumption", "Computer science", "Fuel efficiency", "Routing (electronic design automation)", "Operations research", "Transport engineering", "Engineering", "Automotive engineering", "Computer network" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2111.13050" }, { "id": "https://openalex.org/W7172275060", "doi": "10.5281/zenodo.21774286", "title": "Hybrid Truck–Drone Transportation - Innovative Research on Transportation using Trucks and Drones", "year": 2026, "publication_date": "2026-08-03", "type": "software", "language": null, "authors": [ "Academia EduSoft" ], "first_author": "Academia EduSoft", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Interactive semantic map of truck-and-drone last-mile delivery, TSP/FSTSP optimisation, OR-Tools route planning, Haversine aerial distances, launch and recovery overheads, computational experiments in Bacău County, and future large-scale logistics extensions.", "keywords": [ "Drone", "Truck", "Key (lock)", "Global Positioning System" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.21774286" }, { "id": "https://openalex.org/W4388103307", "doi": "10.2139/ssrn.4589264", "title": "Air Corridor Planning for Urban Drone Delivery: Complexity Analysis and Comparison via Multi-Commodity Network Flow and Graph Search", "year": 2023, "publication_date": "2023-01-01", "type": "preprint", "language": "en", "authors": [ "Lishuai Li", "Xinyu He", "Yanfang Mo", "Zhankun Sun", "S. Joe Qin" ], "first_author": "Lishuai Li", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Computer science", "Drone", "Flow network", "Graph theory", "Algorithm", "Graph", "Theoretical computer science", "Mathematics", "Mathematical optimization", "Combinatorics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4589264" }, { "id": "https://openalex.org/W7154963839", "doi": "10.1111/risa.70246", "title": "An Integrated Cloud‐Based Failure Mode and Effects Analysis Framework for Risk Assessment of Unmanned Aerial Vehicle Operations in Urban Logistics Using Group Consensus", "year": 2026, "publication_date": "2026-04-20", "type": "article", "language": "en", "authors": [ "Fei Gao" ], "first_author": "Fei Gao", "venue": "Risk Analysis", "publisher": "Wiley", "abstract": "Unmanned aerial vehicles (UAVs) are increasingly considered for urban logistics, including the delivery of critical medical supplies. However, their safe operation in dense urban environments requires systematic risk analysis that can account for both technological uncertainties and human factors. Conventional failure mode and effects analysis (FMEA) offers a structured way to identify and prioritize risks but is limited by its use of deterministic evaluations and the absence of mechanisms to handle uncertainty or disagreement among experts. To address these limitations, this study develops an integrated cloud-based FMEA framework to UAV logistics operations. The method begins with expert assessments expressed through linguistic terms, which are transformed into cloud models to represent uncertainty more faithfully. A consensus-reaching process is then applied to align divergent expert opinions and establish an aggregated evaluation matrix. To determine the relative importance of risk factors, a hybrid weighting scheme is employed that combines subjective judgments through cloud step-wise weight assessment ratio analysis (SWARA) and objective information through cloud criteria importance through intercriteria correlation (CRITIC). These weights are subsequently integrated into a cloud technique for order similarity to ideal solution (TOPSIS) procedure that produces a transparent ranking of failure modes. The framework is applied to a case study of medical supply delivery UAVs, where it identifies the most critical risks and validates the prioritization through sensitivity and comparative analyses. The results demonstrate that the proposed approach provides a robust and practical decision-support tool for enhancing safety in urban UAV logistics.", "keywords": [ "Weighting", "Ranking (information retrieval)", "Failure mode and effects analysis", "Cloud computing", "Risk assessment", "Process (computing)", "Relation (database)", "Mode (computer interface)", "Analytic hierarchy process" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1111/risa.70246" }, { "id": "https://openalex.org/W4402531807", "doi": "10.20944/preprints202409.0962.v1", "title": "Spatial Analysis of Middle-Mile Transport for Advanced Air Mobility: A Case Study of Rural North Dakota", "year": 2024, "publication_date": "2024-09-12", "type": "preprint", "language": "en", "authors": [ "Raj Bridgelall" ], "first_author": "Raj Bridgelall", "venue": "Preprints.org", "publisher": null, "abstract": "Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using the mostly rural and small urban U.S. state of North Dakota as a case study. The analysis utilized geographic information system (GIS) and spatial optimization models to strategically assign underutilized airports as multimodal freight hubs to facilitate the shift from long-haul trucks to middle-mile air transport. Key findings demonstrate that electronics, because of their high value-to-weight ratio, are ideally suited for air transport. Comparative analysis shows that transport by drones can reduce the average cost per ton by up to 60% compared to traditional trucking. Optimization results indicate that a small number of strategically placed logistical hubs can reduce average travel distances by more than 13% for last-mile deliveries. Cost analyses demonstrate the viability of drones for middle-mile transport, especially on lower-volume rural routes, highlighting their efficiency and flexibility. The study emphasizes the importance of utilizing existing infrastructure to optimize the logistics network. By replacing truck traffic with drones, AAM can mitigate road congestion, reduce emissions, and extend infrastructure lifespan. These insights have critical implications for supply chain managers, shippers, urban planners, and policymakers, providing a decision support system and a roadmap for integrating AAM into logistics strategies.", "keywords": [ "Truck", "Last mile (transportation)", "Drone", "Mile", "Transport engineering", "Multimodal transport", "Flexibility (engineering)", "Geographic information system", "Business", "Computer science", "Geography", "Engineering" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.preprints.org/frontend/manuscript/0d60205f8c95c1c7731ca0b32a54ad60/download_pub" }, { "id": "https://openalex.org/W7162366157", "doi": null, "title": "Το πρόβλημα του πλανόδιου πωλητή με drones", "year": 2023, "publication_date": "2023-01-01", "type": "article", "language": "en", "authors": [ "Αναστασία Μπαφούνη-Κοττά" ], "first_author": "Αναστασία Μπαφούνη-Κοττά", "venue": "Νημερτής", "publisher": null, "abstract": "Drones are a developing technology promising multiple benefits for delivery services. Especially for the last mile delivery problem in logistics, where the rapid growth of e-commerce and parcel delivery have made the last leg of the deliveries network less efficient over the years, unmanned aerial vehicles (UAVs) can become the necessary strategic solution. Drones not only can fly over ground obstacles and avoid traffic, but they are also fast and precise. In contrast with regular means of transporting goods, UAVs are not restricted by infrastructure and can be an eco-friendly solution to small package deliveries. The present work focuses on the Travelling Salesman Problem (TSP) with Drones, which aims to solve the last mile delivery problem in logistics by combining traditional TSP with drone technology. The thesis examines the feasibility and effectiveness of using drones for small package deliveries by optimizing the route of 3 drones and one vehicle to deliver products to 10 customers using AIMMS software. The results of the study are expected to provide valuable insights into the benefits and limitations of using drones in last-mile delivery and offer recommendations for future implementations. A sensitivity analysis will also be conducted to assess the robustness and reliability of the proposed solution.", "keywords": [ "Drone", "Last mile (transportation)", "Robustness (evolution)", "Reliability (semiconductor)", "Work (physics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/10889/24931" }, { "id": "https://openalex.org/W7172292650", "doi": "10.5281/zenodo.21774285", "title": "Hybrid Truck–Drone Transportation - Innovative Research on Transportation using Trucks and Drones", "year": 2026, "publication_date": "2026-08-03", "type": "software", "language": null, "authors": [ "Academia EduSoft" ], "first_author": "Academia EduSoft", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Interactive semantic map of truck-and-drone last-mile delivery, TSP/FSTSP optimisation, OR-Tools route planning, Haversine aerial distances, launch and recovery overheads, computational experiments in Bacău County, and future large-scale logistics extensions.", "keywords": [ "Drone", "Truck", "Key (lock)", "Global Positioning System" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.21774285" }, { "id": "https://openalex.org/W7203772872", "doi": "10.61360/bonighss26202052040801", "title": "Optimization of UAV–UGV Last-Mile Collaborative Delivery under Dynamic Carbon Footprint Constraints: Visual Simulation and Scenario Analysis of Coordinated Air–Ground Unmanned Delivery System", "year": 2026, "publication_date": "2026-08-20", "type": "article", "language": null, "authors": [ "Yu Qiao", "Xinwen Deng", "Xiaoying Huang", "Wanting Chen", "Yimeng Lin", "Zuqiang Luo", "Yuchen Du", "Luyao Li", "Meijun Shen", "Xuanxuan Chen" ], "first_author": "Yu Qiao", "venue": "Global Humanities and Social Sciences", "publisher": null, "abstract": "To address the challenges of operational cost control, safety assurance, and dynamic carbon footprint management in urban last-mile logistics, this study proposes a UAV–UGV air–ground collaborative delivery framework and develops a multi-objective optimization model considering efficiency, safety, and low-carbon performance. A visual simulation platform is constructed using HTML5 Canvas and Three.js, integrating obstacle avoidance, low-altitude UAV delivery, random scenario generation, and dynamic route re-planning modules. Simulation results show that, under an order density of 20 orders/100 km², the proposed strategy reduces total operational time by 33.9% compared with traditional truck delivery and decreases travel distance by 24.3% compared with UAV-only delivery. The unit carbon emission intensity is reduced by 96.4% and 24.3% compared with truck-based and UAV-only delivery modes, respectively. The obstacle avoidance algorithm achieves a 100% success rate in 50 random scenarios, with a path length variation coefficient of 0.132, demonstrating strong robustness. Sensitivity analysis confirms that the model remains stable under ±20% variations in carbon emission factors and carbon trading prices. This study provides a quantitative decision-support framework for unmanned delivery optimization and low-carbon logistics equipment selection. At the same time, it provides a reference for nurturing potential talent for the future.", "keywords": [ "Carbon footprint", "Truck", "Obstacle", "Sensitivity (control systems)", "Scenario analysis", "Footprint", "System dynamics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ojs.bonfuturepress.com/index.php/GHSS/article/download/2052/1358/10090" }, { "id": "https://openalex.org/W7134978947", "doi": "10.71086/iajse/v12i3/iajse1230", "title": "Optimizing Urban Delivery Systems with Innovative Drone Technology for Sustainability", "year": 2025, "publication_date": "2025-09-30", "type": "article", "language": null, "authors": [ "Dr. Kamlesh Kumar Yadav", "Manish Nandy" ], "first_author": "Dr. Kamlesh Kumar Yadav", "venue": "International Academic Journal of Science and Engineering", "publisher": null, "abstract": "The article focuses on the optimization of city logistics using the assistance of drone-delivery solutions on the last mile. The growing pressure to implement efficient and effective delivery systems in the urban centers has shown that there is a need to embrace innovative logistics approaches. This research provides the solution to traffic congestion, delays during the delivery process, and other environmental problems by uniting the use of unmanned aerial vehicles (UAVs). The research will be conducted based on a mixed-method design where the simulation models will be applied in conjunction with the actual case studies to calculate the impacts of the drone application on the time spent on delivery, fuel consumption amounted to, and carbon emissions. The findings indicate that the benefits are enormous considering that the delivery time will be reduced by 40 (75 minutes to 45 minutes) and there will be less fuel consumption by 75 (40 liters to 10 liters) compared to the traditional processes. In addition, the carbon emission was also switch to 72 percent (18 kg CO 2 to 5 kg CO 2) which also saved the total cost of operations by 58 percent. The effect of the distance of the package delivery, the weight of the package and urban infrastructure on the use of drone delivery are also studied in the paper. The results identify the potential of drones to enhance urban mobility, urban sustainability, and cost-efficiency of logistics. The results are applicable to the existing literature on sustainable urban logistics and may be applied to educate policymakers, logistic businesses, and urban planners. The paper concludes by providing recommendations on how the drone delivery systems can be integrated into the already established urban logistics systems to make the operations more sustainable and efficient.", "keywords": [ "Drone", "Sustainability", "City logistics", "Fuel efficiency", "Consumption (sociology)", "Urban sustainability" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://iaiest.com/iaj/index.php/IAJSE/article/download/1847/2499" }, { "id": "https://openalex.org/W3011587924", "doi": null, "title": "Online Shopping and Drone Technology in Russia", "year": 2018, "publication_date": "2018-01-01", "type": "conference-paper", "language": "en", "authors": [ "Haula Kitonsa" ], "first_author": "Haula Kitonsa", "venue": "Electronic scientific archive of UrFU (Ural Federal University)", "publisher": "Ural Federal University", "abstract": "As the escalation of online shopping toils its capacity in Russia, the effectiveness of last mile delivery has gained total attention since it one of the core phase of an effective transaction via online shopping. Last mile delivery is facing a series of stumbling blocks of which the main ones are; poor infrastructure in rural and disaster-stricken areas and extreme climate condition (winter) hence forcing companies, to incur more the costs at this stage than any other stage. The emerging drone technology with tremendous anticipated applications of which one is delivery, may be the ultimate solution to cutting down costs and ease on the difficulties of last mile delivery. However, like any other technological innovation, drone technology is associated with uncertainties which are regarded as risks, several technical and societal concerns and challenges that need to be addressed. The goal of this review paper is to analyze the feasibility of drone technology in last mile delivery by carrying out its SWOT analysis and point out risks that may arise once deployed to delivery. And carry out a comparison between the current legal framework in Russia with that of major international key players in the technology in order to find out the loop holes and possible steps necessary to be taken towards regulating drone delivery in Russia.", "keywords": [ "Drone", "Computer science", "Aeronautics", "Business", "Advertising", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/10995/68084" }, { "id": "https://openalex.org/W2725746197", "doi": null, "title": "An Integrated Navigation Approach for Autonomous Operation of a Parcel Delivery UAV", "year": 2017, "publication_date": "2017-01-01", "type": "conference-paper", "language": "en", "authors": [ "Dieter Moormann" ], "first_author": "Dieter Moormann", "venue": "RWTH Publications (RWTH Aachen)", "publisher": "RWTH Aachen University", "abstract": null, "keywords": [ "Computer science", "Systems engineering", "Real-time computing", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://publications.rwth-aachen.de/search?p=id:%22RWTH-2017-06149%22" }, { "id": "https://openalex.org/W7115810994", "doi": "10.71548/22626", "title": "Optimizing Drone-Enabled Logistics", "year": 2025, "publication_date": "2025-01-01", "type": "dissertation", "language": "en", "authors": [ "Pushkar, Shamik" ], "first_author": "Pushkar, Shamik", "venue": "MacSphere (McMaster University)", "publisher": "McMaster University", "abstract": "The integration of drones into last-mile delivery systems has garnered significant attention across sectors such as e-commerce, healthcare, and emergency logistics. Despite technological advancements and industry investment, widespread adoption remains limited due to regulatory, financial, and operational challenges. This thesis investigates the feasibility and efficiency of drone-assisted delivery under real-world constraints, with a particular focus on regulatory frameworks. Three mathematical models are developed. The first evaluates the impact of no-fly zones and flight distance restrictions on coordinated truck-drone delivery. The second introduces a hybrid logistics model incorporating droneports to facilitate delivery in urban areas with zoning laws. The third addresses a rural healthcare application, proposing a synchronized delivery and scheduling model for livestock vaccine administration, balancing workload among veterinarians. Each model is formulated as a Mixed Integer Linear Program (MILP), with computational experiments validating their performance. Heuristic and matheuristic algorithms are proposed to solve large-scale instances. Results demonstrate that while drones can enhance delivery efficiency and equity, their benefits are significantly influenced by regulatory severity and operational design.", "keywords": [ "Drone", "Scheduling (production processes)", "Workload", "Heuristic", "Operational efficiency", "Integer programming", "Job shop scheduling", "Zoning" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://macsphere.mcmaster.ca/items/d899bac9-4b92-4c35-9619-25a9d1e656b1/request-a-copy?bitstream=3497b4a8-0b94-426f-8b7d-e70382272d88" }, { "id": "https://openalex.org/W4415300121", "doi": "10.1145/3760550.3760553", "title": "A Lightweight Microchained Architecture for Unmanned Aerial Vehicle Network Reputation Systems", "year": 2025, "publication_date": "2025-06-25", "type": "conference-paper", "language": null, "authors": [ "Simeon Ogunbunmi", "Ronghua Xu", "Yu Chen" ], "first_author": "Simeon Ogunbunmi", "venue": null, "publisher": null, "abstract": "Unmanned Aerial Vehicle (UAV) networks are widely adopted for diverse applications in modern Internet of Things (IoT) ecosystems, ranging from last-mile deliveries to infrastructure inspections. The growing reliance on UAVs makes a secure and trustworthy network environment essential. However, deploying a practical reputation framework in resource-constrained UAV networks necessitates a lightweight, high-throughput, and scalable solution. This paper introduces a Lightweight Microchained ARchitecture (LiMAR) for UAV network reputation systems. LiMAR presents a novel lightweight microchained blockchain model optimized for UAV networks, addressing key blockchain overheads such as storage bloat, high validation costs, and consensus delays. By separating operational data from on-chain transactions, LiMAR reduces computational complexity while maintaining security through reputation-driven consensus. LiMAR is designed to minimize overhead while maintaining key blockchain properties such as immutability and auditability. By incorporating a streamlined consensus mechanism and modular block structure, LiMAR significantly reduces computational and communication costs. This enables UAV nodes to efficiently store and validate reputation scores, even under dynamic flight conditions and limited resource availability. We demonstrate the effectiveness of LiMAR through extensive simulations, evaluating parameters such as latency, throughput, and energy consumption. The results show that LiMAR outperforms conventional blockchain-based solutions in UAV network environments, supporting real-time, decentralized reputation management with minimal resource overhead. This work paves the way for more secure, resilient, and scalable UAV service delivery, underscoring the potential of lightweight blockchain solutions in next-generation IoT deployments.", "keywords": [ "Scalability", "Key (lock)", "Overhead (engineering)", "Architecture", "Reputation", "Resilience (materials science)", "Block (permutation group theory)", "Modular design", "Blockchain" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dl.acm.org/doi/pdf/10.1145/3760550.3760553" }, { "id": "https://openalex.org/W7117993257", "doi": "10.3390/su18010461", "title": "A Comprehensive Review of Building the Resilience of Low-Altitude Logistics: Key Issues, Challenges, and Strategies", "year": 2026, "publication_date": "2026-01-02", "type": "article", "language": "en", "authors": [ "Jingshuai Yang", "Haofeng Xu" ], "first_author": "Jingshuai Yang", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Low-altitude logistics (LAL), supported by unmanned aerial vehicles (UAVs) and emerging urban air mobility operations within the low-altitude airspace (typically <1000 m), is rapidly reshaping last-mile distribution and time-critical delivery. However, LAL systems remain vulnerable to compound disruptions spanning weather, infrastructure, governance, and cybersecurity. Using a PRISMA-guided protocol, this systematic review synthesizes 1600 peer-reviewed studies published from 2020 to 2025 and combines bibliometric mapping (VOSviewer) with qualitative content analysis to consolidate the knowledge base on low-altitude logistics resilience (LALR). We conceptualize LALR via four coupled pillars, including robustness, adaptability, recoverability, and redundancy. The synthesize evidence across key vulnerability domains consists of platform reliability, communication and infrastructure readiness, regulatory fragmentation, cyber exposure, and weather-driven operational uncertainty. Building on the synthesis, we propose a Technology–Policy–Ecosystem roadmap that links (i) AI-enabled autonomy and risk-aware planning, (ii) adaptive governance tools such as regulatory sandboxes and dynamic airspace/UTM management, and (iii) ecosystem-level interventions, notably public–private partnerships and equity-oriented service design for underserved areas. We further outline a research agenda centered on measurable resilience metrics, activate redundancy design, climate-adaptive UAV operations, and digital-twin-enabled orchestration for scalable and sustainable LAL ecosystems.", "keywords": [ "Orchestration", "Resilience (materials science)", "Key (lock)", "Drone", "Critical infrastructure", "Vulnerability (computing)", "Corporate governance", "Scalability", "Urban resilience" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/18/1/461/pdf" }, { "id": "https://openalex.org/W2612960064", "doi": null, "title": "Drones reveal efficiency savings in delivery services", "year": 2015, "publication_date": "2015-07-12", "type": "conference-paper", "language": "en", "authors": [ "Wolfgang Garn" ], "first_author": "Wolfgang Garn", "venue": "Surrey Research Insight Open Access (The University of Surrey)", "publisher": "University of Surrey", "abstract": "Drone delivery services (DDS) are an upcoming reality. Companies such as Amazon, DHL and Google are investing in developments in this area. German’s parcel delivery company DHL has begun applying them commercially. This emphasises the importance to have insights in the economic benefits of drone delivery services. This study compares drone delivery services with traditional delivery services. It looks at the cost effectiveness of integrating drones into a delivery services’ operations. The study identifies and categorise factors that control the delivery operations. It develops a mathematical model that compares 3D flight paths of a fleet of drones with a fleet of 2D van routes. The developed method can be seen as an extension of the Vehicle Routing Problem (VRP). Efficiency savings of drone services of real world rural postcode sectors are analysed. The study limits itself to the use of small unmanned aerial vehicles (UAVs) with a low payload, which are GPS controlled and autonomous. The case study shows time, distance and cost savings when using drones rather than delivery vans. The model reveals efficiency factors to operate DDS. The study shows the economic necessity for delivering low weight goods via DDS. The primary methodological novelty of this study is a model that integrates factors relevant to drones into the VRP.", "keywords": [ "Drone", "Payload (computing)", "Operations research", "Global Positioning System", "Computer science", "Transport engineering", "Engineering", "Computer security", "Telecommunications" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://epubs.surrey.ac.uk/808168/1/SRI_deposit_agreement.pdf" }, { "id": "https://openalex.org/W4366090936", "doi": "10.3920/978-90-8686-943-5_10", "title": "Responsible civilian drones", "year": 2023, "publication_date": "2023-04-17", "type": "book-chapter", "language": "en", "authors": [ "Bart F.W. Wernaart", "Roberta Vaznyte", "Melchior B.C.J. van Velzen", "Isa L.G. Dantuma" ], "first_author": "Bart F.W. Wernaart", "venue": null, "publisher": null, "abstract": "Drones, or unmanned aerial systems, are increasingly used in public spaces, in particular in the context of so-called ‘smart cities’. Drone technology is rapidly innovating, and its hypothetical use in the near future is promising. Drones can be exploited for public and business purposes, e.g. for emergency medication delivery, general last mile delivery, building inspections, the cleaning of solar panels, agricultural applications, surveillance and so on. However, there are some challenges and concerns that relate to fundamental human rights. First, there is the risk of dual use: drones have a military origin, and this technology is now being further used and developed in a civilian setting. The values embodied in these technologies do not automatically reflect societal needs. Furthermore, there are technological challenges that need to be overcome in order to successfully exploit commercial drone services. These challenges make the near-future use of drones an uncertain phenomenon for the average citizen. Third, there is the perception of citizens: while there is some technological optimism, there are grave concerns about privacy and safety, and a call for clear regulation of drone flights. However, it seems that regulators are struggling to keep pace with the innovation. Recent EU initiatives to regulate the so-called U-space give us a glimpse of what the legal concepts will look like in the near future. To conclude, we strongly emphasise the importance of the citizen’s voice in the design process of new drone technologies and services. We offer some Eindhoven-based (the Netherlands) examples of joint research initiatives into which we integrate the values of citizens in drone development.", "keywords": [ "Drone", "Context (archaeology)", "Pace", "Exploit", "Business", "Engineering", "Computer security", "Political science", "Internet privacy", "Computer science", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://brill.com/downloadpdf/book/9789086869435/BP000011.pdf" }, { "id": "https://openalex.org/W4392452383", "doi": "10.1063/5.0194810", "title": "Traveling salesman problem with a moving depot: A mathematical formulation and a saving-based algorithm", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Batool Madani", "Malick Ndiaye" ], "first_author": "Batool Madani", "venue": "AIP conference proceedings", "publisher": "American Institute of Physics", "abstract": "The increase in the use of e-commerce has raised the pressure on logistics providers to resolve the problem of Last Mile Delivery, that is complex and generates high operational costs.The introduction of autonomous vehicles in designing novel distribution systems brings new opportunities for enhancing the existing delivery systems.Logistics providers suggest the inclusion of drones in delivery processes such as truck-drone systems.Therefore, we introduce a single truck and single drone delivery system and solve its related routing problem.In specific, the objective is to minimize the traveling cost of the combined delivery system while determining the optimal sequence of deliveries and optimizing -based heuristics are then provided to solve instances of practical sizes for the problem under consideration.", "keywords": [ "Travelling salesman problem", "Depot", "Computer science", "Mathematical optimization", "Algorithm", "Traveling purchaser problem", "Bottleneck traveling salesman problem", "Mathematics" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1063/5.0194810" }, { "id": "https://openalex.org/W2808806964", "doi": "10.7939/r3319sh94", "title": "Dynamic Image Based Visual Servoing with Unmanned Aerial Vehicles", "year": 2018, "publication_date": "2018-01-01", "type": "dissertation", "language": "en", "authors": [ "Kenny Leung" ], "first_author": "Kenny Leung", "venue": "ERA: Education and Research Archive (University of Alberta)", "publisher": "University of Alberta", "abstract": "In recent years rotary-wing unmanned aerial vehicles (UAVs) are seeing more uses in applications such as transmission line inspection, event filming, parcel delivery, and search-and-rescue missions. Recent improvements in embedded systems have lead to more research for improving unmanned aerial vehicle (UAV) autonomy. Traditionally for outdoor use, the inertial measurement unit (IMU) with magnetometer, barometer, or global positioning system (GPS) can be used for pose estimation, where the pose estimate is used for motion control. However, in GPS denied environments, such as indoors, other sensors need to be used for acquiring pose of the UAV in the environment. One method to solve for the vehicleâs pose is visual servoing, which uses a camera to collect information about the environment, and estimates the UAVâs pose for control. This thesis implements the proposed dynamic image-based visual servoing (DIBVS) controller in Fink et al. [1] using a newer experimental platform to improve the performance. This new platform utilizes the Robot Operating System (ROS) running on an on-board Nvidia Jetson TX1 (TX1) mini computer with a FLIR Chameleon 3 camera for the computer vision (CV) system. ROS is chosen to create a simple framework that would handle necessary components for the UAV, such as image capture and data transfer, while allowing for minimal software changes to test different algorithms. Using this framework, future research projects using the platform can save time troubleshooting issues testing hardware, and instead focus on problems related to the algorithms being tested. Also, future upgrades to the platform would need minimal changes to the software so long as the new system is able to run ROS. For the experiments, the CV system uses color to identify visual features used to compute image moments which are sent to a PX4 flight management unit (FMU) for control of the UAV over a target. The experimental results are compared to the values found in Fink et al. [1], where the new platform is found to have similar performance to the platform used in the reference paper. This result indicates successful implementation of the DIBVS controller on the new platform with a more modular and flexible CV system.", "keywords": [ "Visual servoing", "Computer vision", "Artificial intelligence", "Computer science", "Aerial image", "Image (mathematics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.7939/r3319sh94" }, { "id": "https://openalex.org/W7197050130", "doi": "10.2139/ssrn.7240038", "title": "Spatially Selective Drone Delivery in Low-altitude Logistics: Built Environment Effects on Operational Costs, Responsiveness, Community Exposure and Equity", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Ji Zhou", "Yinfei Xi", "Yunlong Tang", "Hui Fu", "Nan Zheng" ], "first_author": "Ji Zhou", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Software deployment", "Scheduling (production processes)", "Equity (law)", "Service (business)", "Job shop scheduling", "Public service" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.7240038" }, { "id": "https://openalex.org/W2016359109", "doi": "10.1016/0960-2593(96)84018-3", "title": "Project failures and how to avoid them", "year": 1996, "publication_date": "1996-09-01", "type": "article", "language": "en", "authors": [ "Paul R Williams" ], "first_author": "Paul R Williams", "venue": "Computer Audit Update", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Health care", "Business", "Government (linguistics)", "Pandemic", "Medical emergency", "Computer security", "Emergency management", "Coronavirus disease 2019 (COVID-19)", "Computer science", "Medicine", "Political science" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/0960-2593(96)84018-3" }, { "id": "https://openalex.org/W4411863715", "doi": "10.2139/ssrn.5334807", "title": "Drone and Vehicle Routing Problem with Underground Logistics", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": "en", "authors": [ "Hyeonbin Jeong", "Byung Duk Song" ], "first_author": "Hyeonbin Jeong", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Vehicle routing problem", "Routing (electronic design automation)", "Business", "Aeronautics", "Computer science", "Engineering", "Computer network" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5334807" }, { "id": "https://openalex.org/W3201934041", "doi": null, "title": "A comprehensive review on Involvement of drones in covid 19 pandemics: A comprehensive review on Involvement of drones in covid 19 pandemics", "year": 2021, "publication_date": "2021-09-20", "type": "review", "language": "en", "authors": [ "Ruby Mishra", "Santosh Mohan Jena", "Somesh Mahendra Sant" ], "first_author": "Ruby Mishra", "venue": "SPAST Abstracts", "publisher": null, "abstract": "The core idea of the paper is to create a multi-purpose drone/unmanned aerial vehicle which are used to counter challenges faced by COVID-19. Our work is structured to give insights into our theory method with a constructive form of qualitative research. This work's main contribution lies in the comparative study of many research articles based on the use of drone in different fields specially in sanitization of a large area in a stipulated period  , Thermal screening of people and storing their temperature recorded data in cloud, AI implementation in order to detect abnormal pattern of coughing, heart rate etc and delivery of medicines and necessary essential to quarantined people and migrants this will cause a large-scale implementation of drone delivery may drastically change the business, substituting hundreds of workers, fossil-fuel-powered delivery vehicles, traffic congestion, and centralised distribution centres of drone which performs point A to point B parcel delivery. The challenges faced by drone and its operators during active mission are studied. This study will help others who are new to drones in the covid and medical field.\r\nKeywords: Unmanned Arial vehicle, screening, artificial intelligence, UAS", "keywords": [ "Drone", "Pandemic", "Coronavirus disease 2019 (COVID-19)", "Work (physics)", "Computer security", "Constructive", "2019-20 coronavirus outbreak", "Computer science", "Aeronautics", "Business", "Operations research", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://spast.org/techrep/article/view/1042" }, { "id": "https://openalex.org/W7201915590", "doi": null, "title": "Multi-objective vehicle routing with unmanned aerial vehicles using evolutionary algorithms", "year": 2026, "publication_date": "2026-07-15", "type": "article", "language": "el", "authors": [ "Ασημίνα Ρόδη" ], "first_author": "Ασημίνα Ρόδη", "venue": "Νημερτής", "publisher": null, "abstract": "Η παρούσα διπλωματική εργασία εξετάζει το πολυκριτηριακό Πρόβλημα Δρομολόγησης Οχημάτων με Αυτόνομα Εναέρια Οχήματα (drones) – Vehicle Routing Problem with Drones (VRPD) σε περιβάλλον παράδοσης τελευταίου μιλίου (last-mile delivery). Το σύστημα περιλαμβάνει ομογενή στόλο φορτηγών, καθένα από τα οποία συνεργάζεται με ένα αποκλειστικά αντιστοιχισμένο drone. Λαμβάνονται υπόψη περιορισμοί χωρητικότητας, χρονικός συγχρονισμός φορτηγού–drone, δυναμική αυτονομία πτήσης, ελαστικά χρονικά παράθυρα και χρονικά εξαρτώμενη ταχύτητα των φορτηγών.Το πρόβλημα διατυπώνεται με τρεις αντικειμενικές συναρτήσεις ελαχιστοποίησης: τη συνολική ενεργειακή κατανάλωση των φορτηγών, το συνολικό κόστος διανομής και τον χρόνο ολοκλήρωσης. Για την επίλυσή του αναπτύχθηκαν δύο αλγοριθμικές προσεγγίσεις, οι οποίες συνδυάζουν τη μεταευρετική πολυκριτηριακής βελτιστοποίησης Non-dominated Sorting Genetic Algorithm II (NSGA-II), με δυο ευρέως διαδεδομένες μεταευρετικές τοπικής αναζήτησης, την Adaptive Large Neighborhood Search (ALNS) και την VariableNeighborhood Search (VNS), αντίστοιχα.Η πειραματική αξιολόγηση πραγματοποιήθηκε σε 160 στιγμιότυπα διαφορετικού μεγέθους και χωρικής κατανομής, τόσο υπό κοινό αριθμό γενεών όσο και υπό κοινό χρονικό όριο. Επιπλέον, ο NSGA-II–ALNS εξετάστηκε σε σύνολα 75 και 100 πελατών, στα οποία ο NSGA-II–VNS αδυνατούσε να ανταπεξέλθει εντός λογικών χρονικών ορίων. Η αξιολόγηση βασίστηκε στους δείκτες Hypervolume και Spread, στο μέγεθος του πρώτου μη κυριαρχούμενου μετώπου στο τελικό σύνολο λύσεων, στις τιμές των αντικειμενικών συναρτήσεων και στον χρόνο εκτέλεσης.Τα αποτελέσματα έδειξαν ότι ο NSGA-II–VNS παρουσιάζει πλεονεκτήματα σε ορισμένα προβλήματα μεσαίας κλίμακας, αλλά απαιτεί σημαντικά μεγαλύτερο υπολογιστικό χρόνο.Αντίθετα, ο NSGA-II–ALNS ολοκληρώνει τις εκτελέσεις ταχύτερα, παράγει συνήθως μεγαλύτερα μη κυριαρχούμενα μέτωπα και εμφανίζει ευνοϊκότερη συνολική ισορροπία μεταξύ ποιότητας λύσεων και υπολογιστικού κόστους. Ως εκ τούτου, για το εξεταζόμενο πειραματικό πλαίσιο προκρίνεται ο NSGA-II–ALNS ως η καταλληλότερη συνολική προσέγγιση.", "keywords": [ "Vehicle routing problem", "Drone", "Genetic algorithm", "Sorting", "Evolutionary algorithm", "Routing (electronic design automation)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/10889/32586" }, { "id": "https://openalex.org/W4386966682", "doi": "10.14711/thesis-991013222953403412", "title": "On-Time Delivery by Drone Resupply", "year": 2023, "publication_date": "2023-01-01", "type": "dissertation", "language": "en", "authors": [ "Wenqian Liu" ], "first_author": "Wenqian Liu", "venue": null, "publisher": null, "abstract": "Along with the maturity of technologies, such as the Internet of Things and artificial intelligence, the rapid development of online e-commerce has raised the need for what is known as “smart logistics”. With fewer geographical restrictions, higher delivery efficiency, and greater delivery flexibility, drones are a promising option for achieving fast delivery in last-mile urban logistics. Many leading logistics companies, such as Amazon and FedEx, have carried out experimental projects on drone delivery systems. In academia, various operational models for using drones for delivery have been proposed, including drone-only, truck and drone coordinated systems, and drone resupply. The novelty of drone resupply is that drones transport packages from a depot to trucks en route, and then trucks hand over these packages to customers face by face. Despite its potential benefits, existing studies have been focused on designing solution approaches for the drone resupply problem with a single truck and a single drone. As such, there is a need for further research to explore the potential of drone resupply in real-world applications. In this thesis, we investigate more general drone resupply models for on-time delivery, where a fleet of drones is employed to assist a group of trucks in fulfilling delivery requests within specific delivery deadlines. Considering several practical restrictions in urban areas, we first focus on a situation where each delivery truck follows a predetermined route to deliver packages. To ensure the on-time delivery of packages, trucks are dispatched from the depot at certain cutoff times, even if some packages are not yet available for delivery. Drones are then used to resupply these late available packages to specific trucks en route so as to assure on-time delivery. This raises the problem of drone resupply scheduling, which aims to maximize the total value of the late available packages that can be delivered on time. We formally define the problem and analyze its optimality properties. We develop an exact solution approach based on the time-expanded network flow model and design a greedy heuristic algorithm to solve this problem. A series of computational studies are conducted to validate the efficiency and effectiveness of the proposed solutions. Managerial insights and guidance derived from these studies can help logistics companies to make informed decisions both at strategic and operational levels. The drone resupply model can also be applied to on-time meal delivery. To cope with the delayed deliveries of online meals, we can dispatch drones from restaurants to transport meals to riders en route, and then the riders hand over these meals to customers. Such a problem leads to a drone resupply model with multiple trucks, multiple drones, and multiple depots, with rider routing and drone scheduling optimized jointly. We design a two-phase algorithm to solve the problem efficiently. In the first phase, we identify all possible rider routes, along with the corresponding drone scheduling, for serving order bundles. In the second phase, we use a set covering model to select the best rider routes so that all meals are fulfilled with a minimal delay cost. For the problem with a relatively long service period, we propose a rolling horizon strategy to solve it in a dynamic environment. We conduct computational studies to evaluate the efficiency of the solution method and the effectiveness of the proposed drone-assisted delivery model. The computational results demonstrate that adopting drone resupply in on-time meal delivery could lead to a win-win-win situation, where the delay cost and the traveling distance of riders can be reduced significantly, by as much as 54% and 10%, respectively.", "keywords": [ "Drone", "Aeronautics", "Engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.14711/thesis-991013222953403412" }, { "id": "https://openalex.org/W7207543424", "doi": "10.1016/j.tre.2026.105178", "title": "A tractable model and heuristic for vessel routing with multiple unmanned aerial vehicles", "year": 2026, "publication_date": "2026-09-03", "type": "article", "language": "en", "authors": [ "Bo Ren", "Yantong Li", "Hairui Sun", "Danyu Bai", "Kang Chen" ], "first_author": "Bo Ren", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Simulated annealing", "Spare part", "Heuristic", "Travelling salesman problem", "Routing (electronic design automation)", "Key (lock)", "Baseline (sea)", "Heuristics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S1366554526005168/pdf" }, { "id": "https://openalex.org/W4395471368", "doi": "10.1007/978-3-031-55225-0_2", "title": "The Development of Different Logistics Solutions in E-Commerce", "year": 2024, "publication_date": "2024-01-01", "type": "book-chapter", "language": "en", "authors": [ "Grzegorz Chodak" ], "first_author": "Grzegorz Chodak", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Business", "E-commerce", "Computer science", "World Wide Web" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-55225-0_2" }, { "id": "https://openalex.org/W7170172227", "doi": "10.2139/ssrn.7167986", "title": "A CFD-Based Risk Assessment Framework for Drone Delivery Corridors in Dense Urban Areas: Towards Safe and Sustainable Low-Altitude Logistics", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Yansheng Chen", "Zheng Xu", "Jieling Jin", "Said M. Easa", "Helai Huang", "Ye Li" ], "first_author": "Yansheng Chen", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Risk assessment", "Wind speed", "Wind power", "Field (mathematics)", "Risk management" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.7167986" }, { "id": "https://openalex.org/W4300981958", "doi": "10.18297/etd/3756", "title": "Drone location and scheduling problems in humanitarian logistics.", "year": 2021, "publication_date": "2021-01-01", "type": "dissertation", "language": "en", "authors": [ "Zabih Ghelichi" ], "first_author": "Zabih Ghelichi", "venue": null, "publisher": null, "abstract": "Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, are a promising technology for the last-mile delivery of medical and aid items in humanitarian logistics. In emergency scenarios, like disasters, where transportation networks are destroyed and people are stranded, drones can accelerate the delivery of urgently needed items, e.g., food and water, insulin shots and blood pressure pills, to those trapped in the disaster-affected areas. Drones can also provide logistics services in many non-emergency situations by delivering medical items, e.g., vaccine shots and lab specimens, to remote communities and hard-to-access locations. The contribution of using UAVs goes beyond merely having access to remote and disaster-affected areas. With inexpensive launching infrastructures and no need for on-board pilots, drones can offer an inexpensive, agile, and ready-to-use alternative to traditional last-mile delivery modes. Motivated by the challenges associated with the last-mile delivery of aid items to hard-to-access areas, this dissertation studies the problem of drone-based delivery of aid items, e.g., medical and relief packages, to hard-to-access areas in humanitarian logistics. The main goal of this dissertation is to design the logistics and orchestrate a fleet of drones to provide the timely delivery of items to hard-to-access areas in emergency and non-emergency scenarios. In this dissertation, we develop multiple extensions of a drone location and scheduling problem while taking into account the critical aspects of drone- based delivery systems in humanitarian logistics. These critical aspects include: i) limited coverage range, ii) limited payload capacity, iii) energy consumption, iv) timeliness, and v) uncertainty. Chapter II presents a general case of the drone location and scheduling (DLS) problem for the delivery of aid items in disaster-affected areas. In this chapter, we first develop a time-slot formulation to address the problem of optimally locating drone take- off platforms and concurrently scheduling and sequencing a set of trips for each drone to minimize total disutility for product delivery. We extend a two-period problem of DLS where the platforms can be relocated using useable road networks after the first period in order to provide a higher level of coverage. Chapter III proposes a multi-stop drone location and scheduling (MDLS) problem for the delivery of medical items in rural and suburban areas. In this chapter, we assume drones are allowed to stop at one or multiple charging stations, installed on existing platforms having access to electricity, e.g., streetlights, during each trip in order to improve the drones’ coverage range while", "keywords": [ "Drone", "Humanitarian Logistics", "Last mile (transportation)", "Agile software development", "Mile", "Humanitarian aid", "Computer security", "Emergency management", "Computer science", "Transport engineering", "Operations research", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ir.library.louisville.edu/cgi/viewcontent.cgi?article=5070&context=etd" }, { "id": "https://openalex.org/W4413954103", "doi": "10.13111/2066-8201.2025.17.3.4", "title": "Surrogate-based aerodynamic optimization of proprotor blades for a parcel delivery UAV", "year": 2025, "publication_date": "2025-09-03", "type": "article", "language": "en", "authors": [ "Sooin PARK", "Usama YOUNUS" ], "first_author": "Sooin PARK", "venue": "INCAS BULLETIN", "publisher": "National Institute for Aerospace Research “Elie Carafoli” - INCAS", "abstract": "This study presents a surrogate-based aerodynamic optimization framework for a quad-tiltrotor platform designed for both hover and forward flight. To obtain an optimized blade design in both hover and forward flight conditions, a free wake model is coupled with Gaussian Process Regression (GPR). The framework enables efficient exploration of the design space while maintaining physical fidelity in rotor modeling. The rotor blade geometry is parameterized using piecewise linear functions for twist and taper distributions, allowing localized shape control during optimization. Latin Hypercube Sampling (LHS) is used to generate initial design points, and the surrogate model is iteratively refined using the Expected Improvement criterion. The final optimized blade exhibits a 3.7% improvement in hover figure of merit and a 38.3% increase in cruise propulsive efficiency compared to the baseline blade. These gains result from redistributed twist and chord distributions that enhance spanwise loading and reduce induced power loss. The results demonstrate the efficacy of combining free wake analysis with surrogate modeling for the design of UAV-scale rotorcraft.", "keywords": [ "Aerodynamics", "Computer science", "Aerospace engineering", "Marine engineering", "Surrogate model", "Engineering", "Environmental science", "Simulation", "Machine learning" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.13111/2066-8201.2025.17.3.4" }, { "id": "https://openalex.org/W2952306292", "doi": null, "title": "Design of stations and route planning of unmanned aerial vehicle for postal application in Singapore", "year": 2019, "publication_date": "2019-01-01", "type": "report", "language": "en", "authors": [ "Nur Hannah Nordeen" ], "first_author": "Nur Hannah Nordeen", "venue": "DR-NTU (Nanyang Technological University)", "publisher": "Nanyang Technological University", "abstract": "The rise of e-commerce in Singapore has led to a new form of challenges for the postal delivery network. Although the amount of mail to deliver has increased significantly, local mail courier, Singapore Post lacks measures implemented to ease this load. Additionally, the increase in workload and a shortage of manpower have compromised the quality of delivery and encourage irresponsibility. The purpose of this project was to study the implementation of the UAV in postal services in Singapore. The technology for the deployment of UAV to support postal delivery would improve the current operation and stay relevant with current experimental technological advancements carried out overseas. The deployment of UAV in postal services has proven to improve the delivery operation of some delivery couriers. In this project, the routing of the delivery process was discussed to derive a fast and cost-efficient UAV delivery network in Singapore. Ideation of the delivery method and system, and delivery concepts were analysed to find the most suitable operation for this project. UAVs available in the market were also investigated to propose feasible implementation.", "keywords": [ "Aeronautics", "Transport engineering", "Environmental science", "Remote sensing", "Geography", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/10356/77591" }, { "id": "https://openalex.org/W3142736219", "doi": "10.1109/imoc43827.2019.9317640", "title": "6G and Fog Node Mobile Systems for Cooperative, Autonomous, and Dynamic Applications", "year": 2019, "publication_date": "2019-11-10", "type": "conference-paper", "language": "en", "authors": [ "Thiago R. Raddo", "Rafael Nobrega", "Simon Rommel", "Bruno Cimoli", "Anderson Leonardo Sanches", "Idelfonso Tafur Monroy" ], "first_author": "Thiago R. Raddo", "venue": null, "publisher": null, "abstract": "The sixth generation (6G) mobile systems will be the ultimate technology to support any networking requirement. 6G along with fog computing mobile nodes can support any application and use case within the supply chain delivery, regardless of the systems of systems complexity. In this paper, a holistic end-to-end framework platform based on the integration and leverage of 6G and fog mobile systems for physically-entangled systems is proposed. The framework platform, which relies on 6G fog enabled-delivery drones, terahertz communication, and artificial intelligence technologies, is described. The framework can be applied for highly cooperative, autonomous, and dynamic applications and systems such as supply chain's last mile delivery of goods, harbour cranes, and maritime ports to help increasing access to goods in general, reduce traffic congestion and energy comsumption, and ease CO2emissions from transportation. The proposed framework paves the way towards next generation supply chain management including last mile delivery.", "keywords": [ "Computer science", "Leverage (statistics)", "Last mile (transportation)", "Mobile telephony", "Computer network", "Systems engineering", "Telecommunications", "Engineering", "Mobile radio", "Mile" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://research.tue.nl/en/publications/5c2cae3f-955c-4874-b030-0ed88b7bdc9f" }, { "id": "https://openalex.org/W4410377100", "doi": "10.3934/math.2025486", "title": "Optimizing decision precision with linguistic Pythagorean fuzzy Dombi models", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": "en", "authors": [ "Asima Razzaque", "Umme Kalsoom", "Dilshad Alghazzawi", "Abdul Razaq", "Ghaliah Alhamzi" ], "first_author": "Asima Razzaque", "venue": "AIMS Mathematics", "publisher": "American Institute of Mathematical Sciences", "abstract": "Last-mile distribution is a subject that has drawn significant attention from both academic and industry researchers. There are several reasons for the adoption of drone delivery technology, including the growing number of customers who want more flexible and faster delivery options. Currently, there is a large selection of these models on the market. Therefore, there is a need to develop efficient methods to select the most appropriate drone delivery service. This research employs Dombi aggregation operators (AOs) within the context of linguistic Pythagorean fuzzy sets (LPFS) to tackle issues in drone delivery operations. The incorporation of linguistic concepts within the Pythagorean fuzzy framework improves the precision and dependability of delivery data analysis by providing a more thorough representation of uncertainty, consistent with human intuition and qualitative assessments. The present study presents two novel aggregation operators: the linguistic Pythagorean fuzzy Dombi weighted averaging (LPFDWA) and the linguistic Pythagorean fuzzy Dombi weighted geometric (LPFDWG) operators. Essential structural characteristics of these operators are demonstrated, and important particular cases are described. Furthermore, we developed a systematic approach for handling multi-attribute decision-making issues that incorporate LPF data through the use of the suggested operators. In order to showcase the effectiveness of the developed approaches, we provide a numerical illustration that identifies the top drone delivery service. Finally, we execute an in-depth comparative assessment to evaluate the efficacy of the proposed methods in relation to several established procedures.", "keywords": [ "Pythagorean theorem", "Fuzzy logic", "Computer science", "Linguistics", "Artificial intelligence", "Natural language processing", "Management science", "Mathematics", "Economics", "Philosophy" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "http://www.aimspress.com/aimspress-data/math/2025/5/PDF/math-10-05-486.pdf" }, { "id": "https://openalex.org/W7197795254", "doi": null, "title": "Secure communication scheme for Internet of Drones", "year": 2023, "publication_date": "2023-04-01", "type": "article", "language": "en", "authors": [ "B. Molnár" ], "first_author": "B. Molnár", "venue": "University of Debrecen Electronic Archive (University of Debrecen)", "publisher": "University of Debrecen", "abstract": "The use of unmanned aerial vehicles (UAVs) has increased dramatically in recent years, and their applications have expanded from military service to commercial, scientific, and humanitarian operations. (e.g., Amazon's parcel delivery drones, drones rescue operations in Turkey earthquake) The growth in the number of devices makes it increasingly necessary to protect data and platforms in our daily lives. The current security state shows that the infrastructure is immature, which can lead to severe attacks (SkyJack, GPS attacks against the US drone, hardcoded AES keys with CBC mode in the DJI drones). This research proposes a secure, lightweight, scalable scheme for UAV communication using LoRa technology. The proposed scheme is comprised of two phases. The first phase is device registration, a scalable and robust protocol for drones based on secure Physical Unclonable Function (PUF) and blockchain- based registration. The role of the PUF is to provide the device with the appropriate secret and random values during drone registration. It is a device-specific fingerprint that is stored on a private blockchain. Blockchain technology is used to secure storage and potentially share drones' unique PUF values. The registration results in an ARP table which contains the exchanged symmetric keys. After the registration, the second phase is drone communication, where the drone messages transmitted within the network are encrypted by AES-GCM (Advanced Encryption Standard - Galois/Counter Mode), ensuring that all messages are authenticated and encrypted. We implemented a prototype which used LoRa technology. The prototype includes an ESP-WROOM- 32 development module with Espressif ESP32 dual-core processor, MG90S servo motors, an 8x6 propeller, 1200kv brushless DC motor, 3000 mAh LiPO battery and LoRa RA-02 module. We executed the communication analysis, which shows that our new scheme achieves an efficient result.", "keywords": [ "Drone", "Encryption", "Scalability", "Scheme (mathematics)", "The Internet", "Protocol (science)", "Server" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/2437/351316" }, { "id": "https://openalex.org/W3156076655", "doi": "10.1016/j.ifacol.2020.12.2812", "title": "Bio-inspired Coordination and Control of Autonomous Vehicles in Future Manufacturing and Goods Transportation", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Constantin F. Caruntu", "Carlos M. Pascal", "Anca Maxim", "Ovidiu Păucă" ], "first_author": "Constantin F. Caruntu", "venue": "IFAC-PapersOnLine", "publisher": "Elsevier BV", "abstract": "The will to apply bio-inspired techniques to coordinate and control autonomous X vehicles (AXVs) has increased tremendously during the last decade due to their advantages in the face of complexity in today’s demanding applications. Thus, several bio-inspired approaches for multiple-entities optimization have been proposed in the literature for various limited applications, e.g., drone coordination, mobile robot formation maintenance. In all these strategies, the entities must plan their path and control their movements while coordinating their behavior w.r.t. the other members, and they must avoid collisions, so the task could be very difficult in the unstructured environments present in future manufacturing plants and goods transportation. Future applications of these bio-inspired techniques for coordination and control of AXVs include large warehouses, manufacturing, logistics, last-mile delivery, etc. The AXVs could be grouped to carry larger goods or they can act as swarm members when they do not have a common goal, but they must interact while they move to complete the allocated tasks and intersect their paths with the paths of other entities. As such, this paper illustrates the concept of applying such bio-inspired coordination and control techniques for the development of future manufacturing and goods transportation, a discussion being carried out regarding the advantages and disadvantages of several techniques for their use in specific applications.", "keywords": [ "Task (project management)", "Drone", "Plan (archaeology)", "Control (management)", "Computer science", "Systems engineering", "Engineering", "Artificial intelligence" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ifacol.2020.12.2812" }, { "id": "https://openalex.org/W7214452083", "doi": "10.2139/ssrn.7528475", "title": "The Team Orienteering Problem with Drones", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Xuan Ren", "Ola Jabali", "Roberto Roberti", "Chenhao Zhou" ], "first_author": "Xuan Ren", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Orienteering", "Iterated local search", "Drone", "Heuristic", "Sequence (biology)", "Local search (optimization)", "Truck", "Stackelberg competition" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.7528475" }, { "id": "https://openalex.org/W7155080781", "doi": "10.26258/heal.hua.1080", "title": "Το Τελευταίο Μίλι (Last Mile) στις Αστικές Διανομές μετά την Πανδημία: Εξέλιξη, Προοπτικές και η Στάση των Καταναλωτών", "year": 2024, "publication_date": "2024-03-04", "type": "other", "language": "el", "authors": [ "Ελένη Πολύζου", "Eleni Polyzou" ], "first_author": "Ελένη Πολύζου", "venue": "Harokopio University", "publisher": "Harokopio University of Athens", "abstract": "Υπόβαθρο: Η πανδημία COVID-19 μετασχημάτισε τις εφοδιαστικές αλυσίδες, καθιστώντας δημοφιλή την παράδοση last mile. Σκοπός: Η εξέταση των στάσεων των καταναλωτών έναντι της παράδοσης last mile. Μεθοδολογία: Χορηγήθηκε ένα σχετικό ερωτηματολόγιο σε ένα δείγμα 185 ατόμων του γενικού πληθυσμού. Η χορήγηση του ερωτηματολογίου πραγματοποιήθηκε διαδικτυακά. Το ερωτηματολόγιο αποτελούνταν από κοινωνικοδημογραφικά δεδομένα, ερωτήσεις για τη χρήση του last mile και ερωτήσεις για την αποτίμηση όσον αφορά το last mile. Αποτελέσματα: Αρχικά, η συντριπτική πλειονότητα των συμμετεχόντων φάνηκε να χρησιμοποιεί τις υπηρεσίες last mile, παρά τη σημαντική διακύμανση των φορών που τις έχουν χρησιμοποιήσει το τελευταίο εξάμηνο. Σε γενικές ωστόσο γραμμές, οι συμμετέχοντες της έρευνας είχαν χρησιμοποιήσει τις σχετικές αυτές υπηρεσίες από 1 έως 10 φορές (70.01%). Δεύτερον, υπήρχε μία μεγάλη ετερογένεια σχετικά με την πρώτη φορά χρήσης μιας τέτοιας υπηρεσίας, αφού ορισμένοι συμμετέχοντες είχαν αρχίσει να χρησιμοποιούν την υπηρεσία κατά τη διάρκεια της πανδημίας, άλλοι μετά την πανδημία και, το μεγαλύτερο ποσοστό με 44.3%, πριν από την πανδημία. Περίπου ένας στους τρεις συμμετέχοντες πληροφορήθηκε για πρώτη φορά για τη σχετική αυτή υπηρεσία από το διαδίκτυο, ενώ το 1/4 των συμμετεχόντων πληροφορήθηκε από κάποια εταιρεία. Τα βασικά πλεονεκτήματα της υπηρεσίας είναι η μεγαλύτερη ευκολία και η οικονομία χρόνου. Η περιγραφική ανάλυση οδήγησε στη διαπίστωση πως σχεδόν όλοι οι συμμετέχοντες πήγαιναν για παραλαβή του προϊόντος από την έξυπνη θυρίδα είτε μέσω συμβατικού αυτοκινήτου είτε με τα πόδια. Οι συμμετέχοντες, περίπου 2 στους 3, επιθυμούσαν να φτάνουν σε αυτούς τα προϊόντα μέσω αυτοκινήτου, με τους περισσότερους, συγκεκριμένα το 42,7%, να επιλέγει το ηλεκτρικό αυτοκίνητο. Ελάχιστοι συμμετέχοντες, μόλις το 9.2%, προτίμησαν την ιδιαίτερα καινοτόμο μέθοδο των drone. Μία άλλη διαπίστωση της έρευνας έχει να κάνει με απόσταση που θα δέχονταν να διανύσουν οι συμμετέχοντες για να παραλάβουν ένα προϊόν από μία έξυπνη θυρίδα. Οι συμμετέχοντες δέχονταν να διανύσουν σε γενικές γραμμές πολύ μικρές αποστάσεις, με μόλις το 7.1% των συμμετεχόντων να δεχόταν να διανύσει μία απόσταση μεγαλύτερη των 5 km. Η αποτίμηση των συμμετεχόντων για την παράδοση last mile ήταν ιδιαίτερα θετική, με μόνη παράμετρο που δεν αξιολογήθηκε θετικά την περαιτέρω χρέωση των υπηρεσιών, αφού οι συμμετέχοντες ήταν σε μέτριο βαθμό 9 διαθέσιμοι να πληρώσουν παραπάνω. Τέλος, τα κοινωνικοδημογραφικά χαρακτηριστικά των συμμετεχόντων δεν σχετίζονταν σε μεγάλο βαθμό με την αποτίμησή τους για τις υπηρεσίες last mile, με εξαίρεση το εκπαιδευτικό επίπεδο, αφού οι συμμετέχοντες υψηλότερου εκπαιδευτικού επιπέδου είχαν και πιο θετική αποτίμηση. Συμπεράσματα: Στη χώρα μας, χρησιμοποιούνται οι υπηρεσίες last mile σε ικανό βαθμό. Ωστόσο, ορισμένες προτιμήσεις των χρηστών, όπως η ικανή προτίμηση για παράδοση των προϊόντων με αυτοκίνητα συμβατικής καύσης, ενδεχομένως να είναι επιζήμιες για το περιβάλλον. Περαιτέρω έμφαση πρέπει να δοθεί από όσους χαράσσουν σχετικές πολιτικές στην περιβαλλοντική βιωσιμότητα του last mile.", "keywords": [ "Work (physics)", "Term (time)", "Product (mathematics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.26258/heal.hua.1080" }, { "id": "https://openalex.org/W3125752656", "doi": null, "title": "Drone Taşımacılığı ve Son-Adım Teslimatta Kullanımı", "year": 2020, "publication_date": "2020-12-31", "type": "article", "language": "tr", "authors": [ "Gülsün Nakıboğlu" ], "first_author": "Gülsün Nakıboğlu", "venue": "Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi", "publisher": "Süleyman Demirel University", "abstract": "As one of the fundamental building blocks of modern economy, transportation is a very dynamic research and practice area, and it is open to improvement. In this regard, the last-mile distribution, which is deemed as the final step in shipment routing and usually refers to the movement of goods from the warehouse or retailer to the final customer, is considerably costly and complex in terms of planning due to many constraints, such as the shape and weight differences among products, different delivery regions, long distance, the necessity of delivering products within desired time-windows. Other issues associated with last-mile distribution are traffic congestion, emission amounts, and labour costs. Changing customer profiles and demands, and the increasing amount of online shopping require a more effective last-mile distribution process. With the help of different technological solutions, the issues related to delivery time, cost and environmental damage are tried to be reduced, and the overall process is tried to be made more effective by using various new methods, tools and solutions. Although there is still more work to be done on privacy, security, environmental and technological issues, it seems that the Unmanned Aerial Vehicles, more commonly known as drones, will have a wider usage in last-mile distribution with the help of technological developments and legal regulations developed for them.", "keywords": [ "Last mile (transportation)", "Drone", "Mile", "Process (computing)", "Work (physics)", "Distribution (mathematics)", "Traffic congestion", "Transport engineering", "Computer security", "Business", "Computer science", "Operations research" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dergipark.org.tr/en/download/article-file/1441880" }, { "id": "https://openalex.org/W4298381651", "doi": "10.48550/arxiv.1804.03954", "title": "A Variable Neighborhood Search for Flying Sidekick Traveling Salesman\\n Problem", "year": 2018, "publication_date": "2018-04-11", "type": "preprint", "language": null, "authors": [ "Júlia Cária de Freitas", "Puca Huachi Vaz Penna" ], "first_author": "Júlia Cária de Freitas", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "The efficiency and dynamism of Unmanned Aerial Vehicles (UAVs), or drones,\\npresent substantial application opportunities in several industries in the last\\nyears. Notably, the logistic companies gave close attention to these vehicles\\nenvisioning reduce delivery time and operational cost. A variant of the\\nTraveling Salesman Problem (TSP) called Flying Sidekick Traveling Salesman\\nProblem (FSTSP) was introduced involving drone-assisted parcel delivery. The\\ndrone is launched from the truck, proceeds to deliver parcels to a customer and\\nthen is recovered by the truck in a third location. While the drone travels\\nthrough a trip, the truck delivers parcels to other customers as long as the\\ndrone has enough battery to hover waiting for the truck. This work proposes a\\nhybrid heuristic that the initial solution is created from the optimal TSP\\nsolution reached by a TSP solver. Next, an implementation of the General\\nVariable Neighborhood Search is used to obtain the delivery routes of truck and\\ndrone. Computational experiments show the potential of the algorithm to improve\\nthe delivery time significantly. Furthermore, we provide a new set of instances\\nbased on well-known TSPLIB instances.\\n", "keywords": [ "Drone", "Travelling salesman problem", "Truck", "Variable neighborhood search", "Computer science", "Heuristic", "Variable (mathematics)", "Solver", "Operations research", "Set (abstract data type)", "Metaheuristic", "Mathematical optimization" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1804.03954" }, { "id": "https://openalex.org/W4410326989", "doi": "10.2139/ssrn.5252367", "title": "Simulation-Based Validation of Delivery Drone Energy Consumption", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": "en", "authors": [ "SungHyuk Choi" ], "first_author": "SungHyuk Choi", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Energy consumption", "Computer science", "Consumption (sociology)", "Energy (signal processing)", "Engineering", "Statistics", "Mathematics", "Electrical engineering", "Sociology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5252367" }, { "id": "https://openalex.org/W7113649271", "doi": null, "title": "Solar SkyHaul hybrid drone", "year": 2025, "publication_date": "2025-01-01", "type": "book-chapter", "language": "en", "authors": [ "Masri, Airin Najiha", "Fadzly Helmy, Farra Halissa", "Raszali, Nabila Batrisyia", "Hamzah, Nur Jasmine", "Ariffin, Nurul Azrin" ], "first_author": "Masri, Airin Najiha", "venue": "UiTM Institutional Repositories (Universiti Teknologi MARA)", "publisher": "Universiti Teknologi MARA", "abstract": "Currently, the use of drones helps industries extensively, offering faster operations, improved efficiency, and access to hard-to-reach areas. The Solar SkyHaul, a hybrid solar-powered drone, is one of our products that was created to overcome the problems of traditional drones, including their short battery life, small payloads of capacity, and susceptibility to environmental factors. The drone's integration of lithium-Sulphur batteries and high-efficiency solar panels greatly increases flying time and lowers carbon emissions, both of which are in accordance with international sustainability objectives. Its objective is to provide more dependable and adaptable UAV solutions for delivery, surveillance, agriculture, and emergency response applications. A cargo capacity of up to 15 kg, adaptive mission planning, and real-time environmental sensors for danger identification are among its novel characteristics, which make it appropriate for crucial logistics in remote or disaster-affected locations. According to our survey of 31 respondents, there is considerable support (87.1%) for the use of drones for parcel delivery. Users acknowledge the efficiency and environmental benefits of this technology, although some are concerned about security and weather effects. The potential for commercialization of drones is significant, especially in the courier, medical, and humanitarian sectors where quick, self-sufficient delivery is crucial. By facilitating operations in areas with inadequate infrastructure and reducing operating expenses, Solar SkyHaul has the potential to revolutionize logistics and promote sustainable development objectives. As to conclude, this invention offers a forward-thinking solution for robust, environmentally friendly aerial transport systems by fusing renewable energy, intelligent automation, and sophisticated design.", "keywords": [ "Drone", "Commercialization", "Sustainability", "Renewable energy", "Environmentally friendly", "Sustainable development", "Identification (biology)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ir.uitm.edu.my/id/eprint/119546/1/119546.pdf" }, { "id": "https://openalex.org/W4408425358", "doi": "10.36227/techrxiv.174198429.99319977/v1", "title": "Drones and IoD for Emergency Medical Deliveries in the Humanitarian Context", "year": 2025, "publication_date": "2025-03-14", "type": "preprint", "language": "en", "authors": [ "Sudipa Sarker", "Gyöngyi Kovács", "Grzegorz Trzeciak" ], "first_author": "Sudipa Sarker", "venue": null, "publisher": null, "abstract": "In recent years, the integration of smart connected devices and platforms, such as Unmanned Aerial Vehicles (UAVs) or drones, into the expanding Internet of Things (IoT) network has grown significantly. Drones provide innovative solutions for delivering value-added IoT services across various applications, including monitoring, surveillance, on-demand last-mile delivery, and warehouse inventory management. However, the use of long-range UAV flights with high payload capacities for emergency medical deliveries is still in its early stages, mainly due to technical, regulatory, and operational challenges. This paper presents findings from several simulated long-range drone flights exceeding 1,000 km, carrying payloads of up to 150 kg. Our experiments reveal the technical and operational requirements needed to facilitate emergency medical deliveries using drones. These requirements are detailed through the description of a UAV system designed for long-range, heavy cargo operations and the medical delivery system needed for large-distance flights with high payloads. Together, these systems aim to enable IoT integration into healthcare supply chains, advancing towards the realization of Healthcare 5.0.", "keywords": [ "Drone", "Context (archaeology)", "Medical emergency", "Business", "Geography", "Medicine", "Biology", "Archaeology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.36227/techrxiv.174198429.99319977/v1" }, { "id": "https://openalex.org/W4221031533", "doi": "10.2139/ssrn.4062871", "title": "Modeling Optimal Drone Fleet Size and Analyzing Drone-Truck Fleet Allocation Sustainability Tradeoffs", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Yuval Hadas", "Miguel Figliozzi" ], "first_author": "Yuval Hadas", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Aeronautics", "Fleet management", "Sustainability", "Transport engineering", "Computer science", "Operations research", "Engineering", "Aerospace engineering", "Environmental science" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4062871" }, { "id": "https://openalex.org/W7150835518", "doi": "10.1016/j.dam.2026.08.017", "title": "Complexity analysis of the Line-TSP with Drone Transports", "year": 2026, "publication_date": "2026-08-31", "type": "article", "language": "en", "authors": [ "Anna Katharina Janiszczak", "Stefan Bock" ], "first_author": "Anna Katharina Janiszczak", "venue": "Discrete Applied Mathematics", "publisher": "Elsevier BV", "abstract": "Since last-mile distribution processes in urban areas are rapidly expanding, several novel delivery concepts have been proposed in recent years to improve their efficiency. Among these innovative concepts, the integration of unmanned aerial vehicles (drones) plays a prominent role, as they can enable simultaneous deliveries. However, due to limited experience and complexity avoidance, the first experimental real-world applications of combined drone and truck transports in urban areas should be kept simple by limiting them to transports along a single road. To provide a first basic model for these processes whose computational complexity is analyzed in detail, this paper introduces the Traveling Salesman Problem on the Line with Drone Transports (Line-TSPwD). It extends the well-known Line-TSP by a versatile integration of drone transports. After starting together from a given position, neither the truck's nor the drone's route is given, but must be generated such that all customers are served and that the drone returns to the truck after each drone delivery. The Line-TSPwD minimizes the time when the truck and the drone meet after all customers have been served. The Line-TSPwD distinguishes between the continuous case, where the truck and the drone can meet at any line position, and the discrete case, where these meeting points are limited to the predetermined customer locations. A further distinction is made by assuming either a faster truck or a faster drone, while the service at customer locations can be constrained by time windows that define deadlines and/or release dates. This study provides significant new results that resolve the complexity status of different variants of the new Line-TSPwD. In addition, known results from the literature are significantly strengthened.", "keywords": [ "Drone", "Truck", "Travelling salesman problem", "Limiting", "Service (business)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.dam.2026.08.017" }, { "id": "https://openalex.org/W4405592010", "doi": "10.54254/2755-2721/2024.18741", "title": "Collaborative optimization of urban drone and public transit integration", "year": 2024, "publication_date": "2024-12-19", "type": "article", "language": "en", "authors": [ "Hairu Jin", "Dan Liu" ], "first_author": "Hairu Jin", "venue": "Applied and Computational Engineering", "publisher": null, "abstract": "The efficient and cost-effective delivery of goods ordered online poses a significant challenge in the field of logistics. Many companies are exploring the use of drone technology to streamline delivery times and expenses. In the context of last-mile deliveries, the deployment of drones represents a promising technology that offers environmental and economic advantages. This study focuses on last-mile delivery systems, where a fleet of drones operates in conjunction with public transportation to fulfill customer orders. To address this issue, the paper expands upon a mathematical model based on the Vehicle Routing Problem (VRP). Furthermore, it presents a real-life scenario inspired by Stanford’s transportation paradigm. The findings indicate that optimizing the sequence for visiting customers and public transportation stations has a substantial impact on both remaining power and time efficiency during drone deliveries. Moreover, leveraging public transport vehicles for recharging drones or approaching customers can reduce the required number of drones within service areas, thereby extending their operational lifespan. These results highlight the potential for using public transportation as a mobile charging station to save energy and improve package delivery efficiency in last-mile drone deliveries.", "keywords": [ "Drone", "Transit (satellite)", "Public transport", "Urban transit", "Transport engineering", "Computer science", "Environmental planning", "Regional science", "Geography", "Engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.ewadirect.com/proceedings/ace/article/view/18741/pdf" }, { "id": "https://openalex.org/W4379875621", "doi": "10.2514/6.2023-4408", "title": "Unmanned Aerial Vehicle Routing Problem for Integrated Manned and Unmanned Aircraft Operations", "year": 2023, "publication_date": "2023-06-08", "type": "conference-paper", "language": "en", "authors": [ "Yoshinori Matsuno", "Adriana Andreeva-Mori" ], "first_author": "Yoshinori Matsuno", "venue": null, "publisher": null, "abstract": "View Video Presentation: https://doi.org/10.2514/6.2023-4408.vid Small unmanned aerial vehicles (sUAVs) can potentially be used in a wide range of industrial applications, with a main one being last-mile package delivery systems. This study considers the sUAV-based package delivery systems under integrated operations of manned and unmanned aircraft. A multi-trip time-dependent vehicle routing problem is proposed to address the problem of generating optimal routes for sUAV in the integrated operation. Through numerical simulations of the integrated operation in which helicopter and sUAV missions are performed simultaneously in the same airspace, the optimal routes of sUAV are effectively generated without affecting the helicopter mission.", "keywords": [ "Aeronautics", "Range (aeronautics)", "Systems engineering", "Computer science", "Remotely operated underwater vehicle", "Routing (electronic design automation)", "Aerospace engineering", "Vehicle routing problem", "Engineering", "Mobile robot", "Embedded system", "Artificial intelligence" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2514/6.2023-4408" }, { "id": "https://openalex.org/W7111951387", "doi": null, "title": "Game of (Delivery) Drones: A Game-Based Approach for Supporting Deliberation on the Use of Drones in Logistics", "year": 2025, "publication_date": "2025-09-17", "type": "dissertation", "language": "en", "authors": [ "Nadeem, Taalia" ], "first_author": "Nadeem, Taalia", "venue": "Bournemouth University Research Online (Bournemouth University)", "publisher": "Bournemouth University", "abstract": "This study investigates stakeholder perceptions of delivery drones, focusing on their societal implications and potential to inform policy development. While drones are anticipated to transform last-mile logistics, public understanding of their operational and regulatory challenges remains limited. Current research often adopts a deficit model, emphasising gaining acceptance over meaningful explorations of public concerns. This study addresses this gap by employing Social Representations Theory and Knowledge Co-creation to examine how individuals construct shared understandings of delivery drones through dialogue, media narratives, and social interactions. A qualitative approach was adopted, and a serious board game, The Game of (Delivery) Drones, was developed to engage participants in discussions about drone logistics. The game simulated realistic scenarios, incorporating parameters such as ground risk, energy consumption, and operational challenges. Participants explored these aspects while responding to embedded questions that elicited their views on delivery drones. A total of 11 game-based focus groups were conducted, with 58 participants. In parallel, a media representation study analysed drone-related headlines from three major online UK news sources to contextualise how delivery drones are framed in public discourse. These representations informed the design of game scenarios and served as reference points during participant discussions, particularly when reflecting on dominant narratives around drones. Participants actively explored complex scenarios, collaboratively reflecting on the implications of delivery drones. Gameplay facilitated knowledge co-creation, enabling participants to articulate and negotiate diverse perspectives. Participants expressed concerns about safety, privacy, noise, and socio-economic inequities, contrasting these with media portrayals that often emphasise technological progress while downplaying risks. Essential versus non-essential drone use emerged as a key area of debate, with participants calling for place-specific regulations and clearer policy frameworks. The board game effectively engaged stakeholders and captured nuanced insights into public perceptions of delivery drones. This adaptable tool offers a replicable method for public engagement and policymaking. The findings highlight the importance of participatory approaches in developing equitable, context-sensitive regulations and encourage informed decision-making for emerging transport technologies.", "keywords": [ "Deliberation", "Drone", "Construct (python library)", "Negotiation", "Social media", "Stakeholder", "Focus group", "Perception", "Frame analysis", "Unintended consequences", "Narrative" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://eprints.bournemouth.ac.uk/41600/1/NADEEM%2C%20Taalia_Ph.D._2025.pdf" }, { "id": "https://openalex.org/W7148288629", "doi": "10.5281/zenodo.19387921", "title": "Why Drones Deliver Medicine But Not Pizza", "year": 2026, "publication_date": "2026-04-02", "type": "other", "language": "en", "authors": [ "Daniel Rosehill", "Gemini 3.1 (Flash)", "Chatterbox TTS" ], "first_author": "Daniel Rosehill", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Episode summary: Drone delivery is already a life-saving utility in parts of Africa, but in the US, it's hitting regulatory and economic turbulence. This episode explores why medical drones thrive in Rwanda while consumer pizza drops face a $63 cost problem. We unpack the \"observer\" bottleneck, the physics of battery weight, and the network slicing that keeps drones from falling out of the sky. Show Notes The Future of Delivery Is Here—Just Not Where You Think If you imagine drone delivery, you might picture a futuristic scene from a 90s sci-fi film: a flying vehicle pulling up to your window to drop off dinner. While that specific vision hasn't materialized in most Western cities, the technology of autonomous logistics has quietly revolutionized healthcare in parts of the world that skipped traditional infrastructure entirely. The central theme of modern drone delivery is a stark divergence between two parallel tracks: medical necessity and consumer convenience. In Rwanda, the company Zipline has moved far beyond \"pilot programs\" to become a national utility. Since launching in 2016, Zipline has built a network of distribution centers covering 80% of the Rwandan population. The operation is seamless: a doctor sends a request via WhatsApp, a technician packs a blood box onto a zip-rail launch system, and a drone autonomously flies 15 minutes to a remote clinic. The drone drops the package via parachute and returns home. There is no landing, no hand-off, and no paperwork at the site. This frictionless logistics chain is a lifeline in a country where mountainous terrain and washed-out roads can make a 20-mile truck trip take four hours. By leapfrogging roads, much like many African nations skipped landlines for mobile phones, Rwanda has created a regulatory framework that works because the value proposition is undeniable. In contrast, consumer drone delivery in the United States faces a much steeper climb. While Alphabet's Wing has found success in Australian suburbs like Logan—where large backyards and clear lines of sight make tether drops easy—the US regulatory environment is a different beast. The Federal Aviation Administration (FAA) operates under rules designed for Cessnas and Boeings, not quadcopters. The biggest bottleneck is the \"observer problem.\" For a long time, the FAA required a human pilot to maintain visual line of sight of the drone. Paying a human to stand on a roof and watch a drone deliver a bag of chips destroys the economics of the model. The math on this is brutal. Internal projections from Amazon suggested that, without massive efficiency gains, a single drone delivery could cost $63. This astronomical figure stems from high hardware costs, low utilization, and labor-intensive oversight. Traditional last-mile delivery via UPS or FedEx costs between $2 and $5 per stop. For drones to compete, they need to hit a similar price point, likely requiring a \"20-to-1\" ratio where one operator in a control center monitors twenty to thirty drones simultaneously. Currently, the FAA's trust in autonomous AI isn't high enough to grant those waivers at scale, keeping labor costs high. Even if regulation eases, the hardware presents its own challenges. Commercial delivery drones are not the $200 toys found at malls; they are complex machines costing tens of thousands of dollars. The Amazon MK30, for example, features redundant motors, advanced \"detect and avoid\" sensors (radar and lidar), and airframes capable of flying in light rain. Redundancy is non-negotiable because a drone dropping from the sky onto a pedestrian or pet is a liability nightmare. However, this safety adds weight, and weight is the enemy of flight. The \"Achilles' heel\" of drone delivery is the battery. Lithium-ion batteries are heavy, and the more weight dedicated to power, the less is available for payload. Most commercial drones are capped at carrying five pounds, which covers 85% of Amazon's inventory but excludes larger items like microwaves. Furthermore, weather remains a significant constraint. While drones can handle light rain, thunderstorms and high winds ground the fleet, introducing reliability issues that ground-based vans simply don't face. Connectivity is another critical layer. Urban drones rely on \"network slicing\"—dedicated lanes of 5G bandwidth prioritized for drone command and control—ensuring that a drone's signal isn't throttled by crowds streaming video at a stadium. In rural areas, drones rely on high-frequency radio or satellite links like Starlink. However, the most important safety feature isn't just the connection; it's \"edge intelligence.\" Drones are increasingly edge-heavy, meaning they possess enough on-board processing to make decisions without the cloud. If a connection drops, the drone executes a \"lost link\" protocol: it climbs to a safe altitude, checks GPS, and returns to base or autonomously finds a safe landing zone like an empty field. Ultimately, the future of drone delivery is unevenly distributed. In Rwanda, it is a solved problem saving lives daily. In the US, it remains an expensive, regulatory-heavy experiment slowly finding its footing in specific suburbs. The technology works; the challenge now is integrating it into a complex airspace and an even more complex economic model. Listen online: https://myweirdprompts.com/episode/drone-delivery-medicine-pizza-reality", "keywords": [ "Drone", "Guard (computer science)", "Theme (computing)", "Terrain", "Face (sociological concept)", "Technician", "Marketing buzz", "Hollywood" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.19387921" }, { "id": "https://openalex.org/W3175364236", "doi": "10.1049/pbhe024e_ch13", "title": "Application and development of drones for health services in developing countries", "year": 2020, "publication_date": "2020-08-01", "type": "book-chapter", "language": "en", "authors": [ "Dr Ruchi Saxena" ], "first_author": "Dr Ruchi Saxena", "venue": null, "publisher": null, "abstract": "Unmanned aerial vehicles or drones are all set to transform the healthcare supply chain, to enable last-mile deliveries, not only in remote inaccessible regions but also for the urban communities. From blood packets, vaccines, sputum samples, and to emergency medical supplies, drones are being looked at as an option that can complement existing methodologies for reducing the accessibility gap in healthcare. This chapter shares the work done in healthcare drones across the world. As more demonstrations and experiments are being conducted, national-level policies are being drafted and funds have been directed toward this futuristic technology.", "keywords": [ "Drone", "Health care", "Business", "Computer security", "Computer science", "Economic growth", "Economics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1049/pbhe024e_ch13" }, { "id": "https://openalex.org/W7111844738", "doi": null, "title": "ROBUST ENERGY-AWARE UNMANNED AERIAL VEHICLE ROUTING USING ENSEMBLE WEATHER FORECASTS", "year": 2022, "publication_date": "2022-06-01", "type": "dissertation", "language": null, "authors": [ "Won, David D." ], "first_author": "Won, David D.", "venue": "Calhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School)", "publisher": "Naval Postgraduate School", "abstract": "The Marine Corps seeks to develop energy-aware unmanned aerial vehicle (UAV) routing for last-mile logistics resupply. UAVs have limited range and time on station to execute their assigned mission. To optimize the delivery of supplies to dispersed units, users must optimally utilize the internal energy onboard the UAV while considering external factors such as weather and priorities of resupply requests. Energy-aware UAV routing will increase Marine Corps logistics capabilities during expeditionary advanced base operations (EABO). The current EABO construct places forces within the threat rings of adversary weapon systems. Use of UAVs can allow dispersed forces to operate in the adversary’s threat rings without the stoppage of logistical support. This thesis builds upon the two-layer framework developed in previous theses by Jatho (2020) and Haller (2021) to include ensemble weather forecasts and partial delivery of supplies. The first layer, which solves the boundary value problem to obtain optimal trajectories between all nodes in the network, is solved for each member of the ensemble forecast. The second layer consists of a stochastic vehicle routing problem using the cost matrix from the first layer. This thesis also introduces the notion of partial delivery of supplies in the second layer to allow demand nodes to request multiple packages of supplies that can be delivered by multiple UAVs. Finally, this thesis analyzes various case studies and corresponding results.", "keywords": [ "Routing (electronic design automation)", "Range (aeronautics)", "Adversary", "Boundary (topology)", "Construct (python library)", "Vehicle routing problem" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/10945/70783" }, { "id": "https://openalex.org/W4399144949", "doi": "10.1007/978-981-33-4999-5_59-1", "title": "Free-Space Optical and Optical Networks", "year": 2024, "publication_date": "2024-01-01", "type": "book-chapter", "language": "en", "authors": [ "Yibeltal Chanie Manie", "Cheng-Kai Yao", "Peng‐Chun Peng" ], "first_author": "Yibeltal Chanie Manie", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Space (punctuation)", "Free space", "Computer science", "Physics", "Optics" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-981-33-4999-5_59-1" }, { "id": "https://openalex.org/W7128493058", "doi": "10.21203/rs.3.rs-8454583/v1", "title": "Effectiveness of zipline’s drones’ delivery service in improving postpartum hemorrhage (PPH) management and reducing its related mortality and morbidity: A retrospective cross-sectional survey in Rwanda", "year": 2026, "publication_date": "2026-02-10", "type": "preprint", "language": null, "authors": [ "Nsengiyumva Richard¹", "Nduwayezu Richard²", "Kagame Alexis²", "Uhawenimana Thierry Claudien¹", "UMUKUNZI Alice¹", "Bazirete Olive¹", "Uwineza Angelique³", "Habimana Innocent⁴", "Uwimana Francoise⁵", "Ndimurukundo Bauduine¹", "Nshimiyimana Aboubakar²", "Florence Haruna", "Pedro Kremer⁶" ], "first_author": "Nsengiyumva Richard¹", "venue": "Research Square", "publisher": null, "abstract": null, "keywords": [ "Retrospective cohort study", "Health care", "Drone", "Maternal death", "Pregnancy", "Service (business)", "Service delivery framework", "Nonprobability sampling", "Health facility" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.researchsquare.com/article/rs-8454583/latest.pdf" }, { "id": "https://openalex.org/W7159837646", "doi": "10.37943/25onqv4873", "title": "INTELLIGENT DRONE ROUTE PLANNING IN URBAN ENVIRONMENTS: OPTIMIZATION AND SAFETY", "year": 2026, "publication_date": "2026-03-30", "type": "article", "language": "en", "authors": [ "Manara Seksembayeva", "Zhaksylyk Amangaliyev", "Miras Anuarbekov" ], "first_author": "Manara Seksembayeva", "venue": "Scientific Journal of Astana IT University", "publisher": null, "abstract": "This study develops and evaluates an intelligent route-planning model for unmanned aerial vehicles operating in urban environments with the objective of minimizing total flight time while maintaining flight safety. The proposed approach addresses a practical last-mile delivery scenario in a smart-city context and is implemented using Google OR-Tools within a constrained Traveling Salesman Problem framework. Open geospatial data from OpenStreetMap are used to obtain building geometries, street topology, and available height-related attributes, while meteorological data from OpenWeatherMap are used to account for wind conditions in flight-time estimation. Safe cruising altitude is determined from the maximum surrounding obstacle height with an additional safety margin. If explicit building-height data are unavailable, height is approximated from the number of building levels. A prototype system was developed to visualize routes, estimate route distance, flight time, and delivery cost, and export missions in MAVLink/QGroundControl-compatible format. Experimental scenarios for real delivery points in the Astana metropolitan area, including Astana, Kosshy, and Koyandy demonstrate the practical feasibility of the proposed open-data-driven routing approach and show improvements over a baseline sequential routing strategy. The scientific contribution of the study lies in the integration of open geospatial building data, weather-aware flight-time estimation, and safety-oriented altitude selection into a reproducible urban UAV route-planning framework. The proposed method can support the development of safe and cost-efficient drone delivery services in dense urban environments. Experimental scenarios with increasing numbers of delivery points demonstrated that the proposed method remains computationally efficient, with sub-second solver runtime for the tested cases for practical smart-city logistics applications.", "keywords": [ "Geospatial analysis", "Drone", "Context (archaeology)", "Route planning", "Routing (electronic design automation)", "Obstacle", "Solver", "Trajectory" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.37943/25onqv4873" }, { "id": "https://openalex.org/W4353092256", "doi": "10.48175/ijarsct-8689", "title": "A Survey of Drones Using IOT Technology", "year": 2023, "publication_date": "2023-03-22", "type": "article", "language": "en", "authors": [ "Deepak Sonker", "Vishal Khatri", "Vishal Khatri" ], "first_author": "Deepak Sonker", "venue": "International Journal of Advanced Research in Science Communication and Technology", "publisher": "Shivkrupa Publication's", "abstract": "A Drone is a new invention or era in last recent years which is very effective; Drones are commonly known as Unmanned Aircraft System (UAV) or Flying Robots. Previously Unmanned Aircraft System (UAV) was used by militaries all around the world for different kind of technologies like Intelligence, Surveillance and Reconnaissance Operations. The use of Drones has been using continuously in different and wide areas, like Cargo, Parcel Delivery, Internet provision in remote areas, Emergency Aid, Industrial Asset monitoring pipelines, surveillance in crowded areas, providing food in flooded area and many more. Drones are a microcosm of the Internet of Things(IOT), also it has been realized that Drones have potential to increase the business by using the Technology for their Organizations.", "keywords": [ "Drone", "Internet of Things", "Computer security", "The Internet", "Asset (computer security)", "Computer science", "Aeronautics", "Business", "Engineering", "World Wide Web" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.48175/ijarsct-8689" }, { "id": "https://openalex.org/W4383604645", "doi": "10.15803/ijnc.13.2_216", "title": "Delivery Routing to Reduce Calculation Load of Drones on Divided Logistics Areas for Drone Logistics Networks", "year": 2023, "publication_date": "2023-01-01", "type": "article", "language": "en", "authors": [ "Kazuya Matsutani", "Shigetomo Kimura" ], "first_author": "Kazuya Matsutani", "venue": "International Journal of Networking and Computing", "publisher": null, "abstract": "In a drone logistics system, a message delivery system in which the drone delivers messages for other users on the way to a parcel delivery destination has been proposed. To reduce the complexity of message delivery routes, this paper proposes a message delivery method that divides logistics areas and determines the message delivery routes in each area. The method also makes it possible for a later departure drone and an early departure drone to exchange information to add, cancel, and/or exchange their messages and delivery points. The simulation experiments show that compared with the previous method, the proposed method has lower computational complexity and in contrast, the average travel distance increases by a maximum of 53.6% to 77.9% and so forth.", "keywords": [ "Drone", "Computer science", "Routing (electronic design automation)", "Information exchange", "Operations research", "Computer network", "Telecommunications" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.jstage.jst.go.jp/article/ijnc/13/2/13_216/_pdf" }, { "id": "https://openalex.org/W7122413954", "doi": "10.2139/ssrn.6064655", "title": "REROUTING TRAVELING SALESMAN PROBLEM WITH DRONES", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Nguyen Anh-Tu", "Shih-Hao Lu" ], "first_author": "Nguyen Anh-Tu", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Truck", "Heuristic", "Cluster analysis", "Process (computing)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.6064655" }, { "id": "https://openalex.org/W4415752290", "doi": "10.1002/9781394386451.ch2", "title": "Challenges of Big Data Implementation in Drone‐Based Logistics", "year": 2025, "publication_date": "2025-10-31", "type": "other", "language": "en", "authors": [ "Mani Deepak Choudhry", "M Sundarrajan", "S. Jeevanandham", "V. Saravanan" ], "first_author": "Mani Deepak Choudhry", "venue": null, "publisher": null, "abstract": "Over the last few years, e-commerce has caused issues in cost-effective last-mile delivery. In response, companies are turning towards autonomous delivery technologies such as drones. Drone delivery platforms are poised to cut shipping costs and transit times by exploiting drones’ applicability beyond current use cases. Additionally, the effect of big data on logistics is evident, as large data sets are employed to increase operational efficiency across the supply chain. This chapter summarizes existing works on logistics support by drones, emphasizing research issues and trends currently and in the future. It focuses on the risks and challenges of drones in logistics networks and provides insights into how Big Data can be optimized. Moreover, practical methods of applying Big Data in logistics are presented. The chapter discusses major issues and briefly sketches new research directions for UAV-based package delivery systems.", "keywords": [ "Big data", "Drone", "Supply chain", "Humanitarian Logistics", "Operational efficiency", "Supply chain management", "Integrated logistics support" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/9781394386451.ch2" }, { "id": "https://openalex.org/W7138919291", "doi": "10.2139/ssrn.6348258", "title": "The Single Truck and Drone Trailer Routing Problem", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Alexander Rave" ], "first_author": "Alexander Rave", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Trailer", "Drone", "Truck", "Flexibility (engineering)", "Routing (electronic design automation)", "Vehicle routing problem" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.6348258" }, { "id": "https://openalex.org/W7125929357", "doi": "10.1109/smc58881.2025.11342507", "title": "Priority-Driven Instant Delivery System with Drone Resupply", "year": 2025, "publication_date": "2025-10-05", "type": "conference-paper", "language": null, "authors": [ "Xu Zhang", "Xiaokang Zhou", "Yi Cheng Ren", "Tao Huang" ], "first_author": "Xu Zhang", "venue": null, "publisher": null, "abstract": "The unmanned aerial vehicle (UAV) resupply mode offers a viable alternative to parcel delivery by replenishing ground vehicles at intermediate open-space supply points. Usually, orders are treated as equally important with no guarantees of on-time delivery. In this paper, we propose a priority-based delivery framework to efficiently manage real-time delivery demands with varying priorities. Specifically, this framework integrates a fleet of UAVs for resupply and trucks for final delivery. By considering the inherent priority of orders and their elapsed waiting time, a dynamic priority discipline is introduced and customized to different order contexts. This approach ensures that urgent orders are prioritized to ensure timely fulfillment within their deadlines, while low-prioritized orders can still be completed without excessive waiting. Simulations using a real-world city map of Helsinki, along with mobility features of both trucks and UAVs, show significant performance gains over baseline schemes in terms of on-time delivery rate, average delivery time, and waiting fairness among all orders.", "keywords": [ "Drone", "Truck", "Baseline (sea)", "Delivery system", "Order (exchange)", "Instant" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/smc58881.2025.11342507" }, { "id": "https://openalex.org/W7148458961", "doi": "10.5281/zenodo.19387922", "title": "Why Drones Deliver Medicine But Not Pizza", "year": 2026, "publication_date": "2026-04-02", "type": "other", "language": "en", "authors": [ "Daniel Rosehill", "Gemini 3.1 (Flash)", "Chatterbox TTS" ], "first_author": "Daniel Rosehill", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Episode summary: Drone delivery is already a life-saving utility in parts of Africa, but in the US, it's hitting regulatory and economic turbulence. This episode explores why medical drones thrive in Rwanda while consumer pizza drops face a $63 cost problem. We unpack the \"observer\" bottleneck, the physics of battery weight, and the network slicing that keeps drones from falling out of the sky. Show Notes The Future of Delivery Is Here—Just Not Where You Think If you imagine drone delivery, you might picture a futuristic scene from a 90s sci-fi film: a flying vehicle pulling up to your window to drop off dinner. While that specific vision hasn't materialized in most Western cities, the technology of autonomous logistics has quietly revolutionized healthcare in parts of the world that skipped traditional infrastructure entirely. The central theme of modern drone delivery is a stark divergence between two parallel tracks: medical necessity and consumer convenience. In Rwanda, the company Zipline has moved far beyond \"pilot programs\" to become a national utility. Since launching in 2016, Zipline has built a network of distribution centers covering 80% of the Rwandan population. The operation is seamless: a doctor sends a request via WhatsApp, a technician packs a blood box onto a zip-rail launch system, and a drone autonomously flies 15 minutes to a remote clinic. The drone drops the package via parachute and returns home. There is no landing, no hand-off, and no paperwork at the site. This frictionless logistics chain is a lifeline in a country where mountainous terrain and washed-out roads can make a 20-mile truck trip take four hours. By leapfrogging roads, much like many African nations skipped landlines for mobile phones, Rwanda has created a regulatory framework that works because the value proposition is undeniable. In contrast, consumer drone delivery in the United States faces a much steeper climb. While Alphabet's Wing has found success in Australian suburbs like Logan—where large backyards and clear lines of sight make tether drops easy—the US regulatory environment is a different beast. The Federal Aviation Administration (FAA) operates under rules designed for Cessnas and Boeings, not quadcopters. The biggest bottleneck is the \"observer problem.\" For a long time, the FAA required a human pilot to maintain visual line of sight of the drone. Paying a human to stand on a roof and watch a drone deliver a bag of chips destroys the economics of the model. The math on this is brutal. Internal projections from Amazon suggested that, without massive efficiency gains, a single drone delivery could cost $63. This astronomical figure stems from high hardware costs, low utilization, and labor-intensive oversight. Traditional last-mile delivery via UPS or FedEx costs between $2 and $5 per stop. For drones to compete, they need to hit a similar price point, likely requiring a \"20-to-1\" ratio where one operator in a control center monitors twenty to thirty drones simultaneously. Currently, the FAA's trust in autonomous AI isn't high enough to grant those waivers at scale, keeping labor costs high. Even if regulation eases, the hardware presents its own challenges. Commercial delivery drones are not the $200 toys found at malls; they are complex machines costing tens of thousands of dollars. The Amazon MK30, for example, features redundant motors, advanced \"detect and avoid\" sensors (radar and lidar), and airframes capable of flying in light rain. Redundancy is non-negotiable because a drone dropping from the sky onto a pedestrian or pet is a liability nightmare. However, this safety adds weight, and weight is the enemy of flight. The \"Achilles' heel\" of drone delivery is the battery. Lithium-ion batteries are heavy, and the more weight dedicated to power, the less is available for payload. Most commercial drones are capped at carrying five pounds, which covers 85% of Amazon's inventory but excludes larger items like microwaves. Furthermore, weather remains a significant constraint. While drones can handle light rain, thunderstorms and high winds ground the fleet, introducing reliability issues that ground-based vans simply don't face. Connectivity is another critical layer. Urban drones rely on \"network slicing\"—dedicated lanes of 5G bandwidth prioritized for drone command and control—ensuring that a drone's signal isn't throttled by crowds streaming video at a stadium. In rural areas, drones rely on high-frequency radio or satellite links like Starlink. However, the most important safety feature isn't just the connection; it's \"edge intelligence.\" Drones are increasingly edge-heavy, meaning they possess enough on-board processing to make decisions without the cloud. If a connection drops, the drone executes a \"lost link\" protocol: it climbs to a safe altitude, checks GPS, and returns to base or autonomously finds a safe landing zone like an empty field. Ultimately, the future of drone delivery is unevenly distributed. In Rwanda, it is a solved problem saving lives daily. In the US, it remains an expensive, regulatory-heavy experiment slowly finding its footing in specific suburbs. The technology works; the challenge now is integrating it into a complex airspace and an even more complex economic model. Listen online: https://myweirdprompts.com/episode/drone-delivery-medicine-pizza-reality", "keywords": [ "Drone", "Guard (computer science)", "Theme (computing)", "Terrain", "Face (sociological concept)", "Technician", "Marketing buzz", "Hollywood" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.19387922" }, { "id": "https://openalex.org/W3176709068", "doi": null, "title": "Development of autonomous drone for multipurpose functions", "year": 2018, "publication_date": "2018-06-01", "type": "book", "language": "en", "authors": [ "Kai Sheng Sim" ], "first_author": "Kai Sheng Sim", "venue": "Universiti Sains Malaysia Institutional Repository (Universiti Sains Malaysia)", "publisher": "Universiti Sains Malaysia", "abstract": "Autonomous drones can carry out functions such as emergency aid delivery, parcel delivery or inspection works with the help of global positioning system (GPS) location tracker, along with \\nsensors for object avoidance. This thesis provides understanding of UAV and the mechanisms that work together to enable its flight, elaborates the different functions that the autonomous drone is designed to carry out, performs flight data analysis from flash logs on Mission Planner (MP) and Google Earth, and discusses how different objectives – including building the UAV model by considering suitable hardware, object avoidance using HC-SR04 or Maxbotix ultrasonic sensor with Arduino IDE, real-time GPS tracking of drone with Ardupilot (APM) software – are achieved with the current state of technology. The drone uses Raspberry Pi (RPi3) as the processor and a stackable flight controller, Navio2 by Emlid to control its flight. Navio2 is a well-documented, latest developed flight controller (FC) by Emlid, with an array of built-in sensors to assist through different autopilot missions. Advanced Inertial Measurement Unit (IMU) feeds real time flight data to the processor as well as the Ground Control Station (GCS). Global Navigational Satellite System (GNSS) receiver accepts satellites’ signal to pinpoint location of UAV, assist the UAV’s flight over waypoints (WP) in auto modes, and override inaccurate flight parameters through Extended Kalman Filter (EKF). With an external 915 MHz radio telemetry in place flight data can be monitored from GCS even without the need of \\na Local Area Network (LAN) connection. The drone utilises a 12-channel AT10-II RCtransmitter and receiver pair by RadioLink Electronics to enable manual or semi-autonomous control and initiation operations of autonomous mode. A reliability study of the drone is carried out based on failure tree and criticality analysis. The drone is successfully set on mission on GPS tracking and path planning in autonomous mode and is able to respond to obstacles in the object avoidance mode with suitable pitch and roll values based on detected distances.", "keywords": [ "Drone", "Computer science", "Artificial intelligence", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://eprints.usm.my/53384/1/Development%20Of%20Autonomous%20Drone%20For%20Multipurpose%20Functions_Sim%20Kai%20Sheng_E3_2018.pdf" }, { "id": "https://openalex.org/W2772974537", "doi": "10.33012/2017.15269", "title": "A New Path Planning Algorithm Based on GNSS Localization Error Map", "year": 2017, "publication_date": "2017-11-03", "type": "conference-paper", "language": "en", "authors": [ "Guohao Zhang", "Li‐Ta Hsu" ], "first_author": "Guohao Zhang", "venue": "Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)", "publisher": null, "abstract": "The mission of the future parcel delivery will be performed by UAV. However, the GNSS localization in urban area usually experience the notorious multipath effect and non-line-of-sight (NLOS) reception which could potential cause about 50 meters of positioning error. This misleading localization result can be hazardous for UAV applications in the GNSS-challenged areas. However, due to the complexity of multipath, there is no general solution to eliminate the effect. A solution for guiding unmanned aerial vehicle (UAV) operation in the urban area is to plan an optimal route that smartly avoided the area with the dangerous multipath effect. To achieve this goal, the impact of multipath effect in terms of positioning error at different locations must be understood. One method is to simulate the reflection route by ray-tracing algorithm with the aids of predicted satellite positions and the widely available 3D building model. Thus, the multipath effect in pseudorange domain can be simulated using the reflection route and multipath noise envelope according a correlator design. By the reconstructing the multipath-biased pseudorange, the simulated positioning error could be obtained using least square positioning algorithm. Thus, the GNSS error distribution of a wide target area can be further constructed. With the positioning error distribution and 3D building models, an optimal path that avoided not only obstacles but also high multipath effect area can be planned. Both new A* and potential field path planning algorithms are developed to combine with the GNSS error distribution. For the former one, this paper designs a new cost function to consider both the distance to destination and the positioning error at each grid. For the potential field algorithm, a new repulsive field considered both obstacles and high positioning error is developed. By comparing the conventional and the proposed path planning algorithms, the proposed methods can plan paths with less positioning error, namely safer routes for UAV in urban areas.", "keywords": [ "Pseudorange", "Multipath propagation", "GNSS applications", "Non-line-of-sight propagation", "Computer science", "Multipath mitigation", "Algorithm", "Real-time computing", "Satellite", "Global Positioning System", "Remote sensing", "Telecommunications" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.ion.org/publications/pdf.cfm?articleID=15269" }, { "id": "https://openalex.org/W2986158670", "doi": "10.48550/arxiv.1911.05624", "title": "Multi-Purpose Aerial Drones for Network Coverage and Package Delivery", "year": 2019, "publication_date": "2019-11-13", "type": "preprint", "language": "en", "authors": [ "Mohammadjavad Khosravi", "Hamid Saeedi", "Hossein Pishro-Nik" ], "first_author": "Mohammadjavad Khosravi", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "Unmanned aerial vehicles (UAVs) have become important in many applications including last-mile deliveries, surveillance and monitoring, and wireless networks. This paper aims to design UAV trajectories that simultaneously perform multiple tasks. We aim to design UAV trajectories that minimize package delivery time, and at the same time provide uniform coverage over a neighborhood area which is needed for applications such as network coverage or surveillance. We first consider multi-task UAVs for a simplified scenario where the neighborhood area is a circular region with the post office located at its center and the houses are assumed to be uniformly distributed on the circle boundary. We propose a trajectory process such that if according to which the drones move, a uniform coverage can be achieved while the delivery efficiency is still preserved. We then consider a more practical scenario in which the delivery destinations are arbitrarily distributed in an arbitrarily-shaped region. We also do not assume any restrictions on the package arrivals. We show that simultaneous uniform coverage and efficient package delivery is possible for such realistic scenarios. This is shown using both rigorous analyses as well as simulations.", "keywords": [ "Drone", "Computer science", "Trajectory", "Process (computing)", "Last mile (transportation)", "Real-time computing", "Boundary (topology)", "Wireless network", "Wireless", "Simulation", "Mile", "Telecommunications" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1911.05624" }, { "id": "https://openalex.org/W4295895359", "doi": "10.1016/j.trd.2022.103457", "title": "Corrigendum to “Comparison of energy demands of drone-based and ground-based parcel delivery services” [Transp. Res. Part D: Transp. Environ. 78 (2020) 102209]", "year": 2022, "publication_date": "2022-09-15", "type": "erratum", "language": "en", "authors": [ "Thomas Kirschstein" ], "first_author": "Thomas Kirschstein", "venue": "Transportation Research Part D Transport and Environment", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Environmental science", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trd.2022.103457" }, { "id": "https://openalex.org/W4313564944", "doi": "10.2139/ssrn.4312992", "title": "Split Delivery Application in Vehicle Routing Problem with Drones", "year": 2023, "publication_date": "2023-01-01", "type": "preprint", "language": "en", "authors": [ "Yiliang Yuan" ], "first_author": "Yiliang Yuan", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Vehicle routing problem", "Computer science", "Routing (electronic design automation)", "Computer network", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4312992" }, { "id": "https://openalex.org/W4312207705", "doi": "10.5281/zenodo.7486901", "title": "Split Delivery Application in Vehicle Routing Problem with Drones", "year": 2022, "publication_date": "2022-08-25", "type": "article", "language": "en", "authors": [ "Yiliang Yuan", "Jiahang Xie" ], "first_author": "Yiliang Yuan", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "The use of drones for last-mile parcel delivery has attracted popularity of attention, especially among online retailers and food delivery platforms that pursuit a fast and high-quality one-to-one service. However, previous works disregarded or assumed the load capacity of drones as fixed values for simplification in truck-drone delivery, such that there is no split delivery assignments on drones. Yet in real-world applications, considering drone endurance and payload capacity, it is highly practical that they deliver in a split way. This paper concerns the novel variant: the split delivery vehicle routing problem with drones (VRPD-S). We deal with the cases where each truck is equipped with a single drone, for serving a set of customers with minimal delivery duration. This problem is challenging since drones can perform multiple deliveries for a single customer node, i.e., the customers' demands are allowed to be split. Whereas trucks follow the vehicle routing problem and meanwhile need to synchronize with drones at the depot or demand points. We model this problem as a mixed-integer linear program and implement a problem-guided predictive search combined with an adaptive large neighborhood search (PS-ALNS) procedure to solve it. Extensive computational experiments were carried out on benchmark instances available in the literature. According to the numerical results, our model is validated and the proposed algorithm works effectively in small and larger instances. Split deliveries can generate savings both in terms of number of vehicles and travel costs, and lead to more flexible and efficient results for the overall delivery system.", "keywords": [ "Drone", "Vehicle routing problem", "Routing (electronic design automation)", "Computer science", "Computer network", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.7486901" }, { "id": "https://openalex.org/W3042458164", "doi": "10.1109/ccgrid49817.2020.000-4", "title": "Improved Matrix-based Attribute Reduction Algorithm Based on Minimal Elements for Mobile Edge Computing", "year": 2020, "publication_date": "2020-05-01", "type": "conference-paper", "language": "en", "authors": [ "Yi Xu", "Zhiqiang Zheng", "Yan Cheng" ], "first_author": "Yi Xu", "venue": null, "publisher": null, "abstract": "With the development of Internet of Thlngs(IoT) technology, the Mobile Edge Computing (MEC) environment plays an important role in different scenarios. This paper focus on the \"last-mile\" delivery scenario in logistics. In this scenario, due to the limited computation ability of the unmanned aerial vehicle (UAV), high real-time and computational resource-intensive tasks such as obstacle avoidance, route planning, and face recognition are require the assistance by MEC computing resources. However, due to the limited computing power of edge servers, the computing tasks of neural networks has very high delay. It cause the deadline of neural networks computation task may not be satisfied. Besides with the users and environment changed continuously, the neural nework take a long time to update which may affect the work of UAV. Therefore, It is an critical problem to accelerate the calculation and update of neural network on edge server. This paper proposes an attribute reduction algorithm based on rough set, which can reduce redundant attributes and compress the dimensionality of data. The experimental results show that can accelerate the calculation and update of neural network significantly and save the energy consumption.", "keywords": [ "Computer science", "Edge computing", "Mobile edge computing", "Artificial neural network", "Server", "Reduction (mathematics)", "Distributed computing", "Enhanced Data Rates for GSM Evolution", "Computation", "Real-time computing", "Algorithm", "Computer network" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/ccgrid49817.2020.000-4" }, { "id": "https://openalex.org/W7161412505", "doi": "10.1016/j.jestch.2026.102389", "title": "Design and development of a hybrid eVTOL UAV with guided parachute delivery for urban logistics", "year": 2026, "publication_date": "2026-05-16", "type": "article", "language": "en", "authors": [ "Turan Konyalıoğlu", "Sinan Alnıpak", "Erdinç Altuğ" ], "first_author": "Turan Konyalıoğlu", "venue": "Engineering Science and Technology an International Journal", "publisher": "Elsevier BV", "abstract": "In recent years, we have seen various urban parcel delivery solutions designed to overcome the limitations of ground transportation and meet the surge in delivery demand. Many of the proposed systems are in the form of conventional unmanned aerial vehicles (UAVs). Multirotor UAVs typically suffer from limited endurance and range, whereas fixed-wing platforms require runways and lack hovering capability, restricting their applicability in dense urban environments. This paper presents the design and development of a hybrid electric vertical take-off and landing (eVTOL) UAV with a 3.6-m wingspan, combining vertical take-off and landing capability with efficient fixed-wing cruise performance. To eliminate time-consuming landing operations and enhance point-delivery precision, the proposed system integrates a dual parachute-assisted payload deployment mechanism, enabling the delivery of two independent packages without landing. An integrated design framework is adopted, combining aerodynamic modeling, mechanical design, hybrid composite-additive manufacturing, and flight control algorithms. The aerodynamic characteristics of the aircraft are obtained through a unified database generated using the Vortex Lattice Method (VLM), Computational Fluid Dynamics (CFD), and nonlinear simulation environments. Based on this model, trim analysis and stability characteristics are derived and utilized in the controller design. A hierarchical control architecture incorporating Model Predictive Control (MPC), Linear Quadratic Regulator (LQR), and Proportional–Integral–Derivative (PID) controllers is implemented to manage hover, transition, and forward-flight. The proposed system is evaluated through nonlinear simulations conducted in Gazebo and ROS, as well as indoor experimental stability tests. Simulation results demonstrate stable transition behavior, with hover-to-cruise transition completed in 15 s and a maximum altitude deviation of ± 3 m. Trajectory tracking performance across multiple flight modes yielded a root mean square error (RMSE) of 0.5–1.5 m. The guided parachute delivery system is validated through dedicated simulations, achieving a Circular Error Probable (CEP) of about 1 m for each independent package under nominal wind conditions of up to 7 m/s. The aircraft is designed to carry a total payload of 8 kg with a demonstrated cruise efficiency of 15 Wh/km and an operational range of 16 km, while maintaining low manufacturing and operational costs under nominal conditions; performance under adverse wind scenarios is reserved for future experimental validation. The results indicate that the proposed hybrid VTOL UAV offers a viable and scalable solution for multi-package urban delivery applications, combining aerodynamic efficiency, control robustness, and manufacturing flexibility.", "keywords": [ "Runway", "Payload (computing)", "Aerodynamics", "Multirotor", "Controller (irrigation)", "Software deployment", "Sequential quadratic programming", "Cruise control", "Vehicle dynamics", "Nonlinear system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jestch.2026.102389" }, { "id": "https://openalex.org/W4395470451", "doi": "10.1007/978-3-031-57996-7_7", "title": "Evaluation of Genetic Algorithm on the Multidrop Truck-Drone Logistic Problem", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "David Sánchez-Wells", "Pedro Luis González Rodríguez", "José Luis Andrade-Pineda" ], "first_author": "David Sánchez-Wells", "venue": "Lecture notes on data engineering and communications technologies", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Computer science", "Genetic algorithm", "Schedule", "Coding (social sciences)", "Plan (archaeology)", "Vehicle routing problem", "Route planning", "Operations research", "Work schedule" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-57996-7_7" }, { "id": "https://openalex.org/W4285196058", "doi": "10.1109/tgcn.2022.3172900", "title": "Edge-Assisted Intelligent Video Compression for Live Aerial Streaming", "year": 2022, "publication_date": "2022-05-09", "type": "article", "language": "en", "authors": [ "Zhibin Liu", "Mingkai Wang", "Fei Chen", "Qian Lu" ], "first_author": "Zhibin Liu", "venue": "IEEE Transactions on Green Communications and Networking", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The ultra-low latency transmission, high speed broadband and ubiquitous access points in modern cities have greatly alleviated the last mile problem of live streaming services. Yet, the sophisticated video compression of high definition videos is still inevitable before transmission, which leads to overwhelming workloads in the light-weighted video collectors. In this paper, we are motivated to explore the computation offloading of live streaming video compression for UAVs, which are featured by limited capacity and fixed trajectory. In particular, the global motion model is utilized for inter frame residual coding instead of motion vector estimation, which usually takes more than 50% computation complexity in traditional H.264/265. We propose an edge-based Joint Video Coding (eJVC) scheme, which can save up to 84.04% encoding complexity of UAV video collector. Specifically, the attention network is used to distinguish foreground blocks and background blocks in the frame. LSTM neural network is used on the edge server to predict the auxiliary data needed by UAV video collector for video coding. In addition, our proposed solution can also accommodate the movement direction change when the control signal is notified in advance. Finally, the prototype system is implemented with the real world data set, and the experiment results show that our proposed solution can significantly save the computation time with little bitrate distortion performance loss.", "keywords": [ "Computer science", "Video compression picture types", "Data compression", "Inter frame", "Real-time computing", "Multiview Video Coding", "Coding (social sciences)", "Video tracking", "Motion compensation", "Video processing", "Computation", "Edge computing" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tgcn.2022.3172900" }, { "id": "https://openalex.org/W4380608810", "doi": "10.1117/12.2683964", "title": "Evaluating the importance of nodes in the urban logistics UAV distribution network based on complex network theory", "year": 2023, "publication_date": "2023-06-14", "type": "conference-abstract", "language": "en", "authors": [ "Longyang Huang", "Siyi Li", "Xiang Zou", "Bozhi Zhao", "Chenglong Li" ], "first_author": "Longyang Huang", "venue": null, "publisher": null, "abstract": "With the rapid development of unmanned aerial vehicles (UAVs) in urban logistics distribution in recent years, it demonstrates that the use of UAVs in this field will realize network operation in the future. However, identifying sites with high importance in the urban logistics UAV distribution networks is a crucial problem in developing this field. To address this, we construct a directional weighted network model of urban logistics drone distribution using basic knowledge of complex networks, with cargo flow between sites as the side weights. Classical statistical characteristic quantities of urban logistics UAV distribution networks are extracted as the evaluation indexes for key node identification in the network. The TOPSIS comprehensive evaluation method is applied to construct the evaluation system of network node importance. Using Chengdu Gaoxin South District as an example, the importance ranking of sites in this zone's urban logistics UAV distribution network is obtained, and suggestions are given on the order of site opening. The identification of key areas is of great reference value for the future development of urban logistics UAV distribution networks.", "keywords": [ "Ranking (information retrieval)", "Complex network", "Node (physics)", "Construct (python library)", "Computer science", "Field (mathematics)", "TOPSIS", "Identification (biology)", "Key (lock)", "Distribution (mathematics)", "Drone", "Transport engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.1117/12.2683964" }, { "id": "https://openalex.org/W3111032549", "doi": "10.1061/9780784483053.411", "title": "Optimization of Vehicle Routing Problem with Drones in Rural Areas", "year": 2020, "publication_date": "2020-12-09", "type": "conference-paper", "language": "en", "authors": [ "Haimei Chen", "Daiwei Hu", "Tingting Zhang" ], "first_author": "Haimei Chen", "venue": "CICTP 2020", "publisher": null, "abstract": "With the development of e-commerce industry and the improvement of rural economic level, rural Internet consumption is booming. However, the “last mile” distribution of rural e-commerce logistics is facing the problems of imperfect infrastructure equipment construction, high logistics distribution cost, and low distribution efficiency. The “last mile” distribution problem has become the biggest obstacle to the development of rural e-commerce logistics. The idea of drone and truck cooperating in distribution undoubtedly provides a new way to solve the problem of “last mile” of rural e-commerce logistics. In this paper, a mathematical model is established for the vehicle routing problem in which drone and truck cooperate with each other in rural areas. The model takes minimizing total cost as the objective function, including different vehicles, multi-trucks, customer accessibility, vehicles’ load constraints, and time limitations. Finally, the optimization solver is used to solve the small-scale example, and the feasibility of the model is proved. The model can provide guidance for rural e-commerce logistics distribution.", "keywords": [ "Drone", "Routing (electronic design automation)", "Vehicle routing problem", "Computer science", "Computer network", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1061/9780784483053.411" }, { "id": "https://openalex.org/W3132325410", "doi": null, "title": "Facility and Routing Decisions in Truck-Drone Distribution", "year": 2020, "publication_date": "2020-08-06", "type": "other", "language": "en", "authors": [ "Vu Bich Na Doan", "Amr Mohammad Taiyeb" ], "first_author": "Vu Bich Na Doan", "venue": "DSpace@MIT (Massachusetts Institute of Technology)", "publisher": "Massachusetts Institute of Technology", "abstract": "Drones have the potential to be major players in the field of last-mile delivery, especially with the rise of e-commerce. However, they face several technological and regulatory restrictions for large-scale implementation. Combining drones with traditional ground delivery vehicles can bridge this gap while achieving significant improvements in distribution cost and speed over vehicle delivery alone. This research project focuses on modeling and solving the Location-Routing Problem with drones as an ancillary mode of delivery. The goal is to develop a model that identifies the optimal locations for the distribution facilities, as well as the set of combined routes that the trucks and drones will follow to deliver parcels to customers. To solve this problem, a two-steps metaheuristic approach is developed and implemented. The customer locations are first grouped into clusters with centroid positions where trucks would park, dispatch, and retrieve the onboard drones that perform the last step of the delivery. Once the optimal truck parking locations are identified, the selection of the optimal distribution facilities and the truck routes are determined simultaneously, by implementing the Multiple Ant Colony Optimization algorithm. The validation of the model revealed high reliability with a 1% average optimality gap from the exact solution. When applying the model to a real road network, with 200 customers and 5 candidate depot locations, the model confirmed a 24% saving in daily distribution costs from adding 3 drones to every delivery truck. The savings opportunity is less sensitive to the number of drones per truck and the drones’ speed, and more sensitive to the trucks’ speed and the drones’ traveling cost per mile. The analysis reveals that adding drones will generate savings as long as the traveling cost of drones is lower than that of trucks at around $4.00 on average for last-mile delivery.", "keywords": [ "Drone", "Truck", "Routing (electronic design automation)", "Distribution (mathematics)", "Computer science", "Aeronautics", "Operations research", "Business", "Transport engineering", "Engineering", "Automotive engineering", "Mathematics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/1721.1/126493" }, { "id": "https://openalex.org/W7154825859", "doi": "10.16356/j.1005-2615.2025.06.001", "title": "Review on Logistics Air Route Planning Methods for Unmanned Aerial Vehicles in Urban Environments", "year": 2025, "publication_date": "2025-12-01", "type": "article", "language": "zh", "authors": [ "ZHAO Yifei", "LI Zhongming", "Ren Xinhui" ], "first_author": "ZHAO Yifei", "venue": "DOAJ (DOAJ: Directory of Open Access Journals)", "publisher": null, "abstract": "With the rapid development of urban logistics unmanned aerial vehicle （UAV） transportation， multirotor UAVs， due to their vertical take-off and landing capability and agile maneuverability， have formed air route networks with wide coverage and diverse operational modes in many cities. However， urban low-altitude airspace is constrained by high-rise buildings， complex terrain， and dynamic wind fields. It also faces practical challenges such as communication interruptions and low public acceptance. These factors make scientific air route planning a key component for ensuring operational safety and efficiency. First， this study reviews the air route design schemes of major domestic operators. It extracts the basic characteristics of the spatial layout and the sequential connection of functional segments within logistics air routes， and defines a parameterized structural model for logistics air routes. Second， through a literature review， this study summarizes the key factors influencing air route planning， including ground impact risk， weather conditions， public acceptance， and infrastructure. It also examines the main planning methods for en-route air routes and departure/arrival air routes， together with their applicability， advantages， and disadvantages. Third， the study develops an integrated logistics air route planning framework. This framework includes airspace， air routes， and air route networks， covering both en-route air routes and departure/arrival air routes. The findings of this study provide methodological guidance for future theoretical research and practical operations.", "keywords": [ "Route planning", "Key (lock)", "Component (thermodynamics)", "Agile software development", "Air transport", "Multirotor", "Air traffic control" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doaj.org/article/0201b77ca1384aada23d114bc316dac8" }, { "id": "https://openalex.org/W4385267485", "doi": "10.1007/978-3-031-36121-0_28", "title": "Metaheuristic Approach for the Location and Routing Problem with Truck and Drones: A Sustainable Perspective", "year": 2023, "publication_date": "2023-01-01", "type": "conference-paper", "language": "en", "authors": [ "Carlos S. Rodríguez-Salcedo", "María F. Giraldo-Quintero", "Laura S. Ortega-García", "María Alejandra Albarracin-Vanegas", "Carlos Alberto Vega-Mejía", "Elyn Lizeth Solano Charris", "Carlos L. Quintero-Araújo" ], "first_author": "Carlos S. Rodríguez-Salcedo", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Metaheuristic", "Drone", "Vehicle routing problem", "Cluster analysis", "Truck", "Computer science", "Routing (electronic design automation)", "Heuristic", "Mathematical optimization", "Last mile (transportation)", "Facility location problem", "Operations research" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-36121-0_28" }, { "id": "https://openalex.org/W7171302762", "doi": "10.3724/sp.j.1249.2026.04451", "title": "Multi-objective location optimization of urban logistics UAV vertiports considering noise and energy constraints", "year": 2026, "publication_date": "2026-07-01", "type": "article", "language": "en", "authors": [ "Wang Lili", "Song Peiqiao", "Tan Lin" ], "first_author": "Wang Lili", "venue": "JOURNAL OF SHENZHEN UNIVERSITY SCIENCE AND ENGINEERING", "publisher": "Science Press", "abstract": "To improve the scientific planning of logistics unmanned aerial vehicle (UAV) vertiports for urban last-mile delivery scenarios, a two-stage multi-objective optimization model is proposed. In the first stage, service coverage and construction cost are taken as the optimization objectives, and a genetic algorithm (GA) is employed to identify the saturation point of coverage growth, thereby determining a reasonable range for the number of vertiports. In the second stage, a noise and energy consumption evaluation model is established by comprehensively considering service coverage, population density, noise propagation factors, elevation differences, and wind-speed disturbances. Based on this model, the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) is adopted to optimize the spatial layout of logistics UAV vertiports under multiple objectives. A case study is conducted using Liushi Town, Wenzhou, China. Three representative solutions are selected from the Pareto-optimal solution set, representing the cost-oriented, environment-oriented scheme, and the coverage-oriented planning strategies, respectively. The results show that the cost-oriented solution achieves the lowest construction cost at the expense of service coverage; the environment-oriented solution reduces noise impacts by avoiding noise-sensitive areas but results in lower delivery efficiency; and the coverage-oriented solution maintains a higher level of service coverage but requires a larger number of vertiports, leading to increased noise exposure. The proposed method provides technical support for logistics UAV vertiport planning in the context of the low-altitude economy.", "keywords": [ "Genetic algorithm", "Sorting", "Noise (video)", "Context (archaeology)", "Energy consumption", "Range (aeronautics)", "Population", "Service (business)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3724/sp.j.1249.2026.04451" }, { "id": "https://openalex.org/W4367319064", "doi": "10.22214/ijraset.2023.51040", "title": "Computer Vision for Increased Efficiency of Delivery Drones Using NVIDIA Jetson Toolkit", "year": 2023, "publication_date": "2023-04-28", "type": "article", "language": "en", "authors": [ "Ameya Shukla", "Akul Athreye" ], "first_author": "Ameya Shukla", "venue": "International Journal for Research in Applied Science and Engineering Technology", "publisher": "International Journal for Research in Applied Science and Engineering Technology (IJRASET)", "abstract": "Abstract: While drone delivery seemed ludicrous a few years ago, it is now a reality in many parts of the United States and throughout the world. Favourable development conditions, because of the FAA's more relaxed and transparent standards, as well as a rise in demand for autonomous last-mile delivery, are propelling drone delivery technology ahead. Consumers who have had the opportunity to experience drone delivery say they prefer the comfort, speed, and positive environmental effect of drone deliveries. Thus, it is very crucial to implement computer vision to increase the efficiency and safety of these delivery drones – and we believe that Jetson toolkit is a fantastic employable solution. Drones now have the processing power for improved object detection and tracking thanks to advances in computer vision and remote sensing. As a result, structured datasets can be used to teach deep learning-based unmanned aerial vehicles to detect objects while in surveillance mode. DNN-based drones have an important function: 3D object detection. After acquiring relevant data into the app, the camera with a trained computer vision model may scan an object utilising 3D object detection. This enables businesses to detect possible risks or things of concern in real time", "keywords": [ "Drone", "Computer science", "Object detection", "Object (grammar)", "Artificial intelligence", "Computer vision", "Real-time computing", "Human–computer interaction", "Pattern recognition (psychology)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.22214/ijraset.2023.51040" }, { "id": "https://openalex.org/W4417052569", "doi": "10.1109/atc67618.2025.11268766", "title": "Potential-Field-Based Formation Control for Unmanned Aerial Vehicle Swarms with a Human-Piloted Leader", "year": 2025, "publication_date": "2025-10-16", "type": "conference-paper", "language": null, "authors": [ "Taku Noguchi", "Masami Yoshida", "Tsuyoshi Yasuda" ], "first_author": "Taku Noguchi", "venue": null, "publisher": null, "abstract": "Unmanned aerial vehicle (UAV) technology has rapidly expanded its applications in disaster response, surveillance, smart cities, logistics, and defense. However, a single UAV is limited in range and functionality, making cooperative swarm operations increasingly important. In dynamic scenarios such as disaster relief, fully autonomous flights along predefined routes may be insufficient, and human intervention is often requiredTo address this need, we propose an adaptive formation control method for heterogeneous UAV swarms, consisting of a human-piloted leader and multiple autonomous followers, based on the potential field method. The proposed approach enables followers to maintain formation while avoiding obstacles and inter-UAV collisions. Simulation results in representative mission scenarios demonstrate improved obstacle avoidance and formation maintenance, confirming the method’s effectiveness. This approach provides a practical foundation for enhancing the efficiency and reliability of UAV swarm operations across various domains.", "keywords": [ "Obstacle avoidance", "Obstacle", "Swarm behaviour", "Collision avoidance", "Reliability (semiconductor)", "Field (mathematics)", "Drone", "Potential field" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/atc67618.2025.11268766" }, { "id": "https://openalex.org/W7168235108", "doi": "10.1016/j.tre.2026.105091", "title": "UAV-based urban logistics service network design under demand and weather-induced supply uncertainty", "year": 2026, "publication_date": "2026-07-14", "type": "article", "language": "en", "authors": [ "Zhijia Tan", "Qinpeng Wang", "Hai Long Yang", "Wei Liu", "Zhichun Li" ], "first_author": "Zhijia Tan", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Stochastic game", "Stochastic programming", "Service (business)", "Supply and demand", "Traffic congestion", "Supply chain", "Service level", "City logistics", "Network planning and design" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2026.105091" }, { "id": "https://openalex.org/W4414879484", "doi": "10.48550/arxiv.2507.17253", "title": "Optimizing Delivery Logistics: Enhancing Speed and Safety with Drone Technology", "year": 2025, "publication_date": "2025-07-23", "type": "preprint", "language": "en", "authors": [ "Maharshi Shastri", "Ujjval Shrivastav" ], "first_author": "Maharshi Shastri", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "The increasing demand for fast and cost effective last mile delivery solutions has catalyzed significant advancements in drone based logistics. This research describes the development of an AI integrated drone delivery system, focusing on route optimization, object detection, secure package handling, and real time tracking. The proposed system leverages YOLOv4 Tiny for object detection, the NEO 6M GPS module for navigation, and the A7670 SIM module for real time communication. A comparative analysis of lightweight AI models and hardware components is conducted to determine the optimal configuration for real time UAV based delivery. Key challenges including battery efficiency, regulatory compliance, and security considerations are addressed through the integration of machine learning techniques, IoT devices, and encryption protocols. Preliminary studies demonstrate improvement in delivery time compared to conventional ground based logistics, along with high accuracy recipient authentication through facial recognition. The study also discusses ethical implications and societal acceptance of drone deliveries, ensuring compliance with FAA, EASA and DGCA regulatory standards. Note: This paper presents the architecture, design, and preliminary simulation results of the proposed system. Experimental results, simulation benchmarks, and deployment statistics are currently being acquired. A comprehensive analysis will be included in the extended version of this work.", "keywords": [ "Drone", "Software deployment", "Key (lock)", "Global Positioning System", "Authentication (law)", "Encryption" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2507.17253" }, { "id": "https://openalex.org/W3116454840", "doi": "10.48550/arxiv.1910.10451", "title": "Unmanned Aerial Vehicles in Logistics: Efficiency Gains and\\n Communication Performance of Hybrid Combinations of Ground and Aerial\\n Vehicles", "year": 2019, "publication_date": "2019-10-23", "type": "preprint", "language": "en", "authors": [ "Manuel Patchou", "Benjamin Sliwa", "Christian Wietfeld" ], "first_author": "Manuel Patchou", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "Unmanned Aerial Vehicles (UAVs) have drastically gained popularity in various\\nIntelligent Transportation System (ITS) applications to improve the safety and\\nefficiency of transportation systems. In this context, the combination of\\nground vehicles, such as delivery trucks, with drones to assist in the last\\nmile pick-up and delivery of the parcels has been recently proposed. While\\naerial vehicles promise increased efficiency based on flexible routes and\\nparallelized operation, highly reliable wireless communication is also required\\nfor the control and coordination of potentially many drones acting in a\\nself-organized way. In this paper, we analyze the improvements procured by\\ndrone usage in parcel delivery compared to traditional delivery and propose a\\nsimulation framework to further quantify the efficiency gains of the parcel\\ndelivery logistics and to analyze the performance of different wireless\\ncommunications options. To this end, we consider a heterogeneous vehicle\\nrouting problem with various constraints. We consider two approaches regarding\\nthe dispatching and recovery of drones and evaluate their benefits as opposed\\nto parcel delivery with a classic truck only. Furthermore, we compare two\\nnetworking technologies for enabling coordination of the self-organizing teams\\nof drones with a realistically modeled environment: one approach relying on\\nbase station oriented Long Term Evolution (LTE) vs. a more decentralized\\nCellular Vehicle-to-Everything (C-V2X) solution. The results show time savings\\nof nearly 40% can be achieved through drone usage and that the negative impact\\nof urban shadowing on network communications in the base station oriented LTE\\napproach can be compensated by leveraging decentralized C-V2X communications\\n", "keywords": [ "Drone", "Truck", "Base station", "Computer science", "Context (archaeology)", "Popularity", "Wireless", "Computer network", "Intelligent transportation system", "Routing (electronic design automation)", "Transport engineering", "Telecommunications" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1910.10451" }, { "id": "https://openalex.org/W4205361983", "doi": "10.1016/j.trpro.2021.11.047", "title": "The Urban Freight Distribution in Medium Size Cities: Descriptive Data Taken From Pamplona (Spain) and Angers (France)", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Adrián Serrano-Hernández", "Thomas Gougeon", "Luís Cadarso", "Angel Alejandro Juan", "Javier Faulín" ], "first_author": "Adrián Serrano-Hernández", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "Medium-size cities around the world are experiencing rapid changes in their urban centers regarding sustainable mobility, pedestrianization of streets, and vehicle-access control to their city center. This situation is particularly important in the last-mile urban distribution in city centers due to the fact that private cars, public transportation, and freight transportation fiery compete for the same space. This article contextualizes this phenomenon in two European medium-size cities: Angers (France) and Pamplona (Spain). The paper also draws the current situation regarding their mobility and freight-delivery systems in their city centers. Thus, an apposite survey has been deployed in both cities in order to collect social perceptions and mobility patterns data. Additionally, we have included a conjoint analysis study for examining the characteristic determinants for aerial (drone) distribution. Likewise, meaningful conclusions can be extracted from the analysis of the results generated by the current analysis. Firstly, we have realized the immediate effects of a recent sustainable urban-mobility plan at Pamplona, which contrasts with the Angers case, where no similar plan has been deployed yet. Secondly, we have focused our attention on the socio-economic factors that determine the mobility in both cities. Thirdly, we have observed, in both cities, a clear preference for electric vehicles and cargo-bikes for driving inside the city center. Finally, there is a rejection to use drones for merchandise delivery.", "keywords": [ "Geography", "Distribution (mathematics)", "Plan (archaeology)", "Transport engineering", "Public transport", "Descriptive statistics", "Business", "Regional science", "Engineering" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2352146521008061/pdf" }, { "id": "https://openalex.org/W7154982881", "doi": "10.1002/rob.70219", "title": "Research on Collision Avoidance Methods for Logistics Unmanned Aerial Vehicle Based on Dynamic Controlled Interactive Collaborative Fusion", "year": 2026, "publication_date": "2026-04-19", "type": "article", "language": "en", "authors": [ "Yuetan Zhang", "Honghai Zhang", "Weibin Tang", "Wei Pan", "Xiaofeng Zhang", "Caiyu Dai", "Yulin Yuan" ], "first_author": "Yuetan Zhang", "venue": "Journal of Field Robotics", "publisher": "Wiley", "abstract": "ABSTRACT As urban air‐traffic density rises, the risk of mid‐air collisions among low‐altitude logistics drones has become a critical concern. We therefore introduce Dynamic Controlled Interactive Collaborative Fusion (DCICF), a framework that couples multimodal perception with Probabilistic Reciprocal Velocity Obstacles (P‐RVO) modeling to enable safe, cooperative flight in dynamic environments. Simulations with 50 static obstacles yielded zero collisions; in dynamic‐obstacle scenarios the collision rate was 0.083 while each drone completed an average of 2.400 missions; and in clustered multi‐drone tasks the collision rate fell to 0.043 with 2.350 missions per drone. Hardware tests further demonstrated an average decision latency of 120–150 ms, minimum separation distances of > 0.8 m indoors and > 1.2 m outdoors, and a 100% mission‐success rate. Relative to state‐of‐the‐art baselines such as DQN, MILP and RRT*, DCICF offers superior safety, real‐time responsiveness, and scalability, making it a robust solution for urban logistics drone operations.", "keywords": [ "Drone", "Collision", "Collision avoidance", "Probabilistic logic", "Latency (audio)", "Fusion", "Reciprocal", "Dynamic decision-making" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/rob.70219" }, { "id": "https://openalex.org/W7167577572", "doi": "10.20858/sjsutst.2026.131.8", "title": "RELIABILITY ANALYSIS OF THE INDICATED AIRSPEED SENSOR IN UNMANNED AERIAL VEHICLES USING NON-PARAMETRIC METHODS", "year": 2026, "publication_date": "2026-06-30", "type": "article", "language": "en", "authors": [ "Anna Michalska", "Robert BRODZIK", "Mariusz Izdebski" ], "first_author": "Anna Michalska", "venue": "Scientific Journal of Silesian University of Technology Series Transport", "publisher": null, "abstract": "Unmanned Aerial Vehicles (UAVs) play an increasingly important role in civil and military aviation, supporting missions ranging from infrastructure monitoring and parcel delivery to reconnaissance and combat operations. Their widespread use in modern transport systems raises the demand for reliable onboard equipment. Among critical subsystems, the Indicated Airspeed (IAS) sensor provides key information for flight control, stability management, and stall prevention. Failures of the IAS sensor – caused by contamination, icing, mechanical damage, or electronic malfunction – pose a significant safety hazard and may lead to flight instability or operational incidents. This study investigates the reliability of the IAS sensor in UAVs using non-parametric reliability analysis methods. Data collected from the SAMANTA maintenance management system over a four-year observation period (2016-2019) were analyzed to determine the cumulative distribution function, hazard rate, and instantaneous reliability function. The research highlights that IAS-related failures account for the second-largest group of recorded UAV malfunctions, underscoring the importance of proactive maintenance strategies. The results provide insights into the operational reliability of IAS sensors and lay the groundwork for the development of predictive maintenance models, improved component design, and enhanced UAV safety in both civil and military applications.", "keywords": [ "Reliability (semiconductor)", "Airspeed", "Hazard", "Hazard analysis", "Aircraft maintenance", "Flight safety", "Key (lock)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.20858/sjsutst.2026.131.8" }, { "id": "https://openalex.org/W4386487775", "doi": "10.1007/978-3-031-43612-3_20", "title": "A Variable Neighborhood Search Algorithm for the Truck-Drone Routing Problem", "year": 2023, "publication_date": "2023-01-01", "type": "conference-paper", "language": "en", "authors": [ "Batool Madani", "Malick Ndiaye" ], "first_author": "Batool Madani", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Routing (electronic design automation)", "Vehicle routing problem", "Variable (mathematics)", "Last mile (transportation)", "Operations research", "Computer network", "Mile", "Engineering", "Automotive engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-43612-3_20" }, { "id": "https://openalex.org/W7124521536", "doi": null, "title": "Consumer acceptance of drone-based food delivery services", "year": 2025, "publication_date": "2025-12-27", "type": "dissertation", "language": "en", "authors": [ "Wenyi Qiu" ], "first_author": "Wenyi Qiu", "venue": "Aaltodoc (Aalto University)", "publisher": "Aalto University", "abstract": "The swift progress in autonomous delivery solutions has drone food delivery envisioning as a revolutionary change in the last-mile logistics. The technical feasibility of drone delivery services is being proved through pilot projects run by food delivery giants, but consumer acceptance is the key factor for large-scale deployment. Still, there is not a lot of empirical re-search investigating the consumers' behavioural intentions regarding the acceptance of drone food delivery. In this paper, the authors are aiming to fill this gap by looking at the psychological and social factors that consumers consider when deciding whether or not to use drone delivery services. The study combines an integrated framework that uses the Technology Acceptance Model along with the Theory of Planned Behaviour to guide the entire process. Through this research, the prior models are augmented by including perceived innovativeness and perceived risk, thus capturing the allure of technological novelties and at the same time, the concerns related to uncertainty and safety. A total of 422 people has participated in an online survey. The data reveal that perceived usefulness, perceived ease of use, and perceived innovativeness have a positive impact on consumer attitudes toward drone food delivery, whereas perceived risk has a significant negative effect on both attitude and perceived behavioral control. Behavioral intention is significantly predicted by attitude, subjective norm, and perceived behavioral control, with attitude being the most important predictor. The integrated TAM–TPB model accounts for a moderate level of variance. Multi-group analysis also confirms that age affects the strength of some of the relationships, indicating that young consumers are influenced more by innovativeness and risk perceptions, while social influence is more significant among older consumers. This research extends the TAM–TPB model in the drone food delivery domain and contributes to the theory by offering an empirical validation. From a management point of view, the results suggest that it is very important to balance the promotion of innovation with the use of trust-building strategies in order to reduce perceived risks and increase consumer acceptance.", "keywords": [ "Food delivery", "Drone", "Technology acceptance model", "Risk perception", "Theory of planned behavior", "Consumer behaviour", "Usability", "Social influence" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://aaltodoc.aalto.fi/handle/123456789/142006" }, { "id": "https://openalex.org/W4416009089", "doi": "10.1117/12.3089263", "title": "An adaptive large neighborhood search algorithm based on multitree genetic programming for solving vehicle routing problems with unmanned aerial vehicles", "year": 2025, "publication_date": "2025-11-07", "type": "conference-paper", "language": null, "authors": [ "Yuxin Liu", "Huipeng Ji" ], "first_author": "Yuxin Liu", "venue": null, "publisher": null, "abstract": "Over the past decade, the use of Unmanned Aerial Vehicles (UAVs), also known as drones, for last-mile delivery has gained increasing popularity in both research and industry. This paper proposes a three-stage hybrid optimization strategy. First, a Multi-tree Genetic Programming (MGP) algorithm is used for dynamic clustering and tree-structure encoding to generate high-quality initial solutions. Then, an improved Adaptive Large Neighborhood Search (ALNS) algorithm, combined with a new string removal operator and a greedy repair strategy, is applied for path optimization. Finally, a Tabu Search (TS) algorithm is employed to focus on optimizing UAV sub-paths, comprehensively handling constraints such as endurance, load capacity, and collaborative waiting. Experimental results show that the hybrid algorithm (MGP-ALNS-TS) outperforms similar algorithms in terms of both optimal objective values and algorithm efficiency.", "keywords": [ "Tabu search", "Greedy algorithm", "Cluster analysis", "Genetic algorithm", "Vehicle routing problem", "Dynamic programming", "Focus (optics)", "Bees algorithm", "Encoding (memory)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1117/12.3089263" }, { "id": "https://openalex.org/W7124236313", "doi": null, "title": "Distributed Adaptive Multi-Drone Coordination At Scale", "year": 2025, "publication_date": "2025-10-01", "type": "dissertation", "language": "en", "authors": [ "Chuhao Qin" ], "first_author": "Chuhao Qin", "venue": "White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)", "publisher": "White Rose University Consortium", "abstract": "Designing and understanding the multi-drone operations is a grand challenge. This is particularly prominent in intelligent transportation systems where swarms of cooperative drones are used for traffic monitoring and last-mile delivery. Although significant technological breakthroughs have been achieved in the control and communication of individual drones, coordinating multiple drones for distributed task allocation remains an open research problem. This involves determining which drones should visit which points of interest on the map, and when, to execute tasks, such as collecting sensing data and inspecting infrastructure, thereby maximizing mission performance (e.g., high completion rate, accurate sensing). Figuring out the best way to allocate these tasks is complex and falls into a class of problems known as NP-hard combinatorial optimization. Previous work addresses this problem by employing distributed task allocation algorithms, from market-based methods to swarm intelligence. However, such approach comes with three key limitations: (1) Poor scalability in large-scale operations: Existing approaches struggle with long-term, large-scale planning due to high computational and communication costs. (2) Poor adaptability to diverse real-world conditions: Current models often overlook or over-simplify real-world factors, such as drone weight, payload and recharging locations, making it difficult to estimate energy consumption and adapt to environmental dynamics. (3) Costly, risky and oversimplified prototyping: Even scalable and adaptive models need real-world testing with low-cost, safe but not oversimplified prototyping to disentangle the complexity of multi-drone coordination before real-world deployment. To address these challenges, this thesis contributes to propose a distributed multi-agent coordination model where each agent/drone independently determines navigation, tasking and recharging plans to choose from such that system-wide requirements are met. The model optimizes the discrete plan selection by integrating state-of-the-art reinforcement learning, collective learning and exact algorithms, which enhances both scalability and adaptability in evolving environments under critical hard constraints. As a proof of concept, this work focuses on two scenarios: traffic monitoring in urban sensing and last-mile delivery in logistics. Experimental results demonstrate that the proposed method achieves scalable, energy-efficient and accurate task execution in large-scale spatio-temporal scenarios (e.g., coordinating 1,000 drone dispatches for full-day, city-sized missions), while operating under limited drone and energy resources. These findings offer valuable insights for policymakers, system operators, and technology designers aiming to enhance intelligent transportation systems. Potential benefits include reducing carbon emissions from heavy vehicles, alleviating traffic congestion, improving the quality of urgent medical deliveries (e.g., pandemics), and informing the optimal placement of recharging stations or depots. Furthermore, the development of an indoor testbed ensures low-cost deployment, operational safety, and the applicability of the proposed system. These advantages are validated through hardware experiments, which confirm accurate energy consumption estimation and minimal collision risk. The proposed testbed bridges the gap between complex algorithmic simulations and practical but oversimplified multi-drone implementations before outdoor testing. It provides a replicable and scalable prototyping, paving the way for broader adoption of advanced multi-drone systems.", "keywords": [ "Scalability", "Drone", "Payload (computing)", "Key (lock)", "Task (project management)", "Adaptability", "Scale (ratio)", "Class (philosophy)", "Swarm behaviour" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://orcid.org/0000-0002-6178-7973" }, { "id": "https://openalex.org/W4414918615", "doi": "10.1007/s13177-025-00558-w", "title": "A Hybrid Metaheuristic Algorithm for Solving Vehicle Routing Problem with Drone (VRPD)", "year": 2025, "publication_date": "2025-10-07", "type": "article", "language": "en", "authors": [ "Ahmad Rahimi Denjkolaei", "Rasul Enayatifar", "Mahdi Golsorkhtabaramiri", "Kamal Jadidy Aval" ], "first_author": "Ahmad Rahimi Denjkolaei", "venue": "International Journal of Intelligent Transportation Systems Research", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Vehicle routing problem", "Benchmark (surveying)", "Metaheuristic", "Heuristic", "Variable neighborhood search", "Greedy algorithm", "Routing (electronic design automation)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s13177-025-00558-w" }, { "id": "https://openalex.org/W7155032939", "doi": "10.57001/huih5804.2025.356", "title": "Reinforcement learning for the traveling salesman problem with drone", "year": 2025, "publication_date": "2025-09-30", "type": "article", "language": null, "authors": [], "first_author": null, "venue": "Journal of Science and Technology - HaUI", "publisher": null, "abstract": "Recently, the problem of transportation routing with integrated drones in IoT-based logistics has emerged as a prominent research area within the academic community.It is particularly important for IoT applications in the transportation and logistics sectors, especially in last-mile delivery.Drones take off from predefined stop points to serve customers and then land at hubs to connect with other vehicles for continued delivery, all while adhering to constraints such as flight range and payload capacity.Integrating drone and vehicle routing poses unique challenges due to the need to synchronize both drone and vehicle schedules to optimize overall delivery time or system costs.In this paper, we introduce the Traveling Salesman Problem with Drone (TSPD) to optimize delivery costs.We then develop two efficient algorithms to address the TSPD.Our Q-learning and Sarsa algorithms enable a drone, transported by a vehicle, to deliver multiple parcels to customers at different locations, with the goal of minimizing delivery costs and maximizing customer satisfaction upon parcel delivery.Through experiments on artificially generated realistic scenarios, the results demonstrate that the proposed algorithms achieve promising computational performance.", "keywords": [ "Drone", "Travelling salesman problem", "Payload (computing)", "Routing (electronic design automation)", "Vehicle routing problem", "Reinforcement learning" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.57001/huih5804.2025.356" }, { "id": "https://openalex.org/W4404875780", "doi": "10.1007/978-981-97-9243-6_8", "title": "Iterated Local Search Metaheuristic for the Vehicle Routing Problem with Drones", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Tomoya Iseki", "Shun Ito", "Kengo Katayama" ], "first_author": "Tomoya Iseki", "venue": "Lecture notes in electrical engineering", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Metaheuristic", "Iterated local search", "Vehicle routing problem", "Local search (optimization)", "Computer science", "Mathematical optimization", "Routing (electronic design automation)", "Iterated function", "Mathematics", "Artificial intelligence", "Computer network" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-981-97-9243-6_8" }, { "id": "https://openalex.org/W7133344849", "doi": "10.1117/12.3101418", "title": "Grid-based location optimization for UAV vertiports in urban logistics networks", "year": 2026, "publication_date": "2026-03-03", "type": "conference-paper", "language": null, "authors": [ "Haotian Li", "Qiqian Zhang", "Honghai Zhang", "Hairu Wang" ], "first_author": "Haotian Li", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Key (lock)", "Global Positioning System", "Trajectory", "Process (computing)", "Work (physics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1117/12.3101418" }, { "id": "https://openalex.org/W4391851149", "doi": "10.31893/multiscience.2024126", "title": "Customisation and payload integration of hexacopter for enhanced grocery delivery", "year": 2024, "publication_date": "2024-01-26", "type": "article", "language": "en", "authors": [ "Sifti Arora", "Efstratios L. Ntantis" ], "first_author": "Sifti Arora", "venue": "Multidisciplinary Science Journal", "publisher": null, "abstract": "The research paper aims to customize the DJI F550 drone for efficient grocery deliveries by incorporating an electrically controlled hook and integrating set coordinates, providing a systematic and precise framework for the drone's navigation and delivery operations. The objectives encompass constructing a hexacopter equipped with a servo hook for payload detachment, creating a mobile application for order management, demonstrating ground operations and communication, and analyzing stress and load-bearing capacity.The primary goal is to automate grocery delivery, ensuring a hassle-free experience for customers in all weather conditions while addressing minimal privacy concerns. The current paper advocates for Urban Logistics, striving to save human resources, reduce customer burden, shorten delivery times, enhance privacy, and minimise delivery risks. Additionally, it explores optimization, including the upgrade of the drone’s battery and remote controller. Stress analysis using CATIA and ANSYS software is presented providing valuable insights into the structural integrity of the drone, revealing key considerations for enhancing performance and reliability. Conclusively, this paper investigates future scalability and commercial applications, ultimately proposing a fully functional drone-based grocery delivery system to revolutionise traditional shopping experience.", "keywords": [ "Payload (computing)", "Business", "Grocery shopping", "Grocery store", "Computer science", "Computer security", "Marketing" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://malque.pub/ojs/index.php/msj/article/download/1746/1087" }, { "id": "https://openalex.org/W4312915297", "doi": "10.2139/ssrn.4240825", "title": "Sustainable Two-Echelon Truck and Drone Routing Problem", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Ebrahim Teimoury", "Reza Rashid" ], "first_author": "Ebrahim Teimoury", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Routing (electronic design automation)", "Vehicle routing problem", "Aeronautics", "Business", "Computer science", "Operations research", "Engineering", "Computer network", "Aerospace engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4240825" }, { "id": "https://openalex.org/W7213925057", "doi": "10.58837/chula.the.2025.599", "title": "Regulatory readiness for drone food delivery in Indonesia", "year": 2025, "publication_date": "2025-01-01", "type": "dissertation", "language": null, "authors": [ "Richo Andriyanto" ], "first_author": "Richo Andriyanto", "venue": null, "publisher": null, "abstract": "This thesis examines the regulatory readiness of Indonesia for the integration of commercial drone food delivery services, employing a comparative analysis with Thailand and using China's adaptive regulatory framework as a benchmark. As the demand for last-mile delivery solutions accelerates in Southeast Asia's rapidly digitising economies, drone technology presents a transformative opportunity to overcome urban congestion and logistical inefficiencies. However, the existing regulatory architecture in Indonesia, principally Law No. 1/2009 concerning Aviation and Minister of Transportation Regulation No. 37/2020, remains fragmented, static, and oriented toward recreational or limited industrial drone use, lacking specific provisions for high-frequency, beyond visual line of sight (BVLOS) commercial operations. Adopting a normative legal research methodology grounded in doctrinal analysis, this study conducts a systematic evaluation of primary legal materials, secondary scholarly literature, and tertiary resources from Indonesia, Thailand, and China. The analytical framework integrates regulation theory, the diffusion of innovation theory, risk management theory, and a functional comparative approach to identify transferable principles rather than imposing foreign rules wholesale. The findings reveal six core regulatory deficiencies in Indonesia's current regime that collectively render the framework incapable of supporting commercial drone food delivery at scale: (1) absence of a legal framework for BVLOS operations, constituting the primary technical-legal barrier to scalability; (2) lack of drone-specific data privacy provisions under the Personal Data Protection Law No. 27/2022; (3) absence of Remote Identification and cybersecurity standards, creating significant security vulnerabilities; (4) liability vacuum for autonomous system accidents, as Law No. 1/2009 contains provisions for manned aviation only; (5) absence of public engagement and nuisance mitigation framework, undermining social acceptance; and (6) institutional fragmentation and enforcement gaps, particularly the dualism of authority between the Ministry of Transportation and the Indonesian National Air Force, which creates a \"regulatory grey zone\" that neither agency can effectively exercise regulatory powers. While Thailand demonstrates a comparatively more developed framework, including remote pilot licensing, weight-based classification, no-fly zones, and pilot project mechanisms, it too exhibits significant gaps in adaptability, risk-proportionate rules, liability clarity, Unmanned Traffic Management (UTM) integration, and data privacy protections. When compared with China's Civil Aviation Administration (CAAC) model, this thesis finds that China's regulatory evolution, characterised by tiered licensing, regulatory sandboxes, mandatory Remote Identification, formalised public-private partnerships, provisional rule-making authority, and iterative, data-driven policymaking, offers instructive and transferable lessons. The thesis proposes concrete legal amendments for Indonesia, including revisions to Article 35 of Law No. 1/2009 to expressly authorise commercial unmanned aircraft operations with risk-proportional delegation, the introduction of new Articles 35A, 35B, and 35C establishing statutory mandates for UTM, Remote ID, and regulatory sandboxes, and the introduction of Article 48A establishing presumptive operator liability, compulsory third-party insurance scaled to risk categories, and joint and several liability for platform companies. Parallel recommendations are advanced for Thailand, including codification of a \"Commercial Delivery Drone Operator\" category, strict liability provisions, and pre-approved urban delivery corridors. Beyond national reforms, the thesis argues for ASEAN harmonisation through a Model Law on Commercial Drone Operations, incorporating standardised risk-based classification, mutual recognition clauses for operator certifications, a common template for third-party liability insurance, and technical standards for interoperability. This thesis calls for an implementation framework which proposes a National Drone Delivery Task Force in Indonesia via Presidential Decree, a specialised Drone Delivery Unit within Thailand's CAAT, joint capacity-building programmes, a three-phase national UTM roadmap (2026-2028), and key performance indicators including license processing time, authorised BVLOS routes, safety incident rates, and operator compliance with data privacy. The thesis addresses state security risks associated with drone operations, including surveillance and espionage, weaponisation and asymmetric warfare, smuggling and transnational crime, critical infrastructure disruption, terrorism, and airspace sovereignty violations. The thesis proposes specific security measures, including mandatory Remote ID, dynamic geofencing, cybersecurity standards, operator vetting, cross-agency coordination, and international cooperation to mitigate these risks while enabling commercial operations. This thesis concludes that Indonesia's regulatory ecosystem is \"partially ready\" in terms of basic airspace management but \"critically unready\" regarding the commercial, operational, liability, institutional, and security complexities of autonomous food delivery systems.", "keywords": [ "Drone", "Liability", "Risk management", "Transformative learning", "Aviation", "Identification (biology)", "Intellectual property", "Best practice", "Law enforcement" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.58837/chula.the.2025.599" }, { "id": "https://openalex.org/W4285821908", "doi": "10.2139/ssrn.4165926", "title": "Time-Dependent Two-Echelon Truck and Drone Routing Problem", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Ebrahim Teimoury", "Reza Rashid" ], "first_author": "Ebrahim Teimoury", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Routing (electronic design automation)", "Vehicle routing problem", "Computer science", "Operations research", "Aeronautics", "Business", "Engineering", "Computer network", "Automotive engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4165926" }, { "id": "https://openalex.org/W4361982566", "doi": "10.35511/978-963-334-450-7_s6_nyikos_ionescu", "title": "Application Areas of Drones: Exploratory Research from Residential and Corporate Perspectives", "year": 2023, "publication_date": "2023-01-01", "type": "book-chapter", "language": "en", "authors": [ "Bendegúz Richárd Nyikos", "Astrid Ionescu" ], "first_author": "Bendegúz Richárd Nyikos", "venue": "Soproni Egyetem Kiadó eBooks", "publisher": null, "abstract": "UAVs (Unmanned Aerial Vehicles), aerial robots, drones - whatever you call them, there is no doubt that their popularity has grown at an astonishing rate in recent years. Although for a very long time they were only seen at military bases and in movies, drones have now conquered the consumer market and revolutionised many industrial sectors. Today, drones are frequently used not only for military missions but also for simple everyday tasks. Whether it's for rapid parcel delivery, aerial damage assessment or even scientific projects, these remote-controlled flying devices offer a whole new range of possibilities for both everyday users and specialists. The paper is based on the review of the relevant literature and aims to explain the fields of application regarding the various flying devices.", "keywords": [ "Drone", "Popularity", "Engineering", "Aeronautics", "Political science", "Law" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://publicatio.uni-sopron.hu/2630/1/MTU_2022_Conf_Proceedings_SOE_LKK_s6_Nyikos_Ionescu.pdf" }, { "id": "https://openalex.org/W4312683597", "doi": "10.1016/j.trpro.2022.11.008", "title": "Auction-based Task Allocation for Safe and Energy Efficient UAS Parcel Transportation", "year": 2022, "publication_date": "2022-01-01", "type": "article", "language": "en", "authors": [ "Marco Rinaldi", "Stefano Primatesta", "Giorgio Guglieri", "Alessandro Rizzo" ], "first_author": "Marco Rinaldi", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "In this paper, two greedy auction-based algorithms are proposed for the allocation of heterogeneous tasks to a heterogeneous fleet of UAVs. The tasks set is composed of parcel delivery tasks and charge tasks, the latter to guarantee service persistency. An optimization problem is solved by each agent to determine its bid for each task. When considering delivery tasks, the bidder aims at minimizing the energy consumption, while the minimization of the flight time is adopted for charge tasks bids. The algorithms include a path planner that computes the minimum risk path for each task-UAV bid exploiting a 2D risk map of the operational area, defined in an urban environment. Each solution approach is implemented by means of two auction strategies: single-item and multiple-item. Considerations about complexity and efficiency of the algorithms are drawn from Monte Carlo simulations.", "keywords": [ "Computer science", "Task (project management)", "Mathematical optimization", "Planner", "Set (abstract data type)", "Auction algorithm", "Path (computing)", "Greedy algorithm", "Energy consumption", "Monte Carlo method", "Operations research", "Common value auction" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2352146522006755/pdf" }, { "id": "https://openalex.org/W7108449316", "doi": "10.57945/manara.hbku.30694316", "title": "Drone vs. Bird Classification and Applied Color Transfer Augmentation", "year": 2025, "publication_date": "2025-01-01", "type": "dissertation", "language": null, "authors": [ "Al-Sulaiti, Muna Abdulaziz Th M." ], "first_author": "Al-Sulaiti, Muna Abdulaziz Th M.", "venue": "Qatar National Library", "publisher": "Qatar National Library", "abstract": "Unmanned Aerial Vehicles (UAVs), commonly known as drones, have rapidly transformed the landscape of both civilian and military operations. Their usage spans a wide range of applications—from commercial photography and agriculture to tactical reconnaissance and parcel delivery. However, their growing accessibility and capabilities pose significant threats in terms of unauthorized surveillance, smuggling, and potential airborne attacks. A critical concern in automated airspace monitoring is the accurate identification of drones, particularly when differentiating them from birds—natural flying entities that share similar aerial dynamics, shapes, and appearances.Distinguishing between drones and birds in aerial images is inherently complex due to overlapping visual characteristics and varied environmental conditions, such as lighting, motion blur, or sensor noise. This thesis addresses this challenge by proposing a deep learning-based classification framework using advanced convolutional neural network architectures. The system employs ResNet-50 and ResNet-152 through transfer learning, allowing efficient feature extraction and training on limited datasets. Furthermore, color transfer techniques are applied to improve model generalization across different domains, especially when dealing with infrared imagery. Detailed experimentation was conducted using original and color-transferred datasets, comprising a balanced distribution of drone and bird imagery. The models demonstrated high classification accuracy, with ResNet-152 achieving superior performance due to its depth. This research contributes to a scalable, adaptable and defensible approach to drone detection and bird classification, laying the foundation for deployment in real-time surveillance and autonomous security systems.", "keywords": [ "Drone", "Software deployment", "Transfer of learning", "Convolutional neural network", "Generalization", "Identification (biology)", "Feature extraction", "Feature (linguistics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.57945/manara.hbku.30694316" } ]