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An Air Route Network Planning Model of Logistics UAV Terminal Distribution in Urban Low Altitude Airspace

Author

Listed:
  • Shan Li

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Honghai Zhang

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Zhuolun Li

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Hao Liu

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

Traditional terminal logistics distribution in urban areas is mainly concentrated on the ground, which leads to increasingly serious air pollution and traffic congestion. With the popularization of unmanned aerial vehicle (UAV) techniques and the reform of low altitude airspace, terminal logistics distribution is expected to be carried out by drones. Therefore, it is of great significance to construct a reasonable air route network for logistics UAV to ensure the safety and efficiency of operations. In this paper, a single route planning model and an air route network planning model for UAV were constructed by fully considering the complex urban low altitude environment, the flight performance of UAV and the characteristics of logistics tasks to regulate the flights of drones. Then, taking Jiangjun Road Campus of Nanjing University of Aeronautics and Astronautics as an example, the improved cellular automata (CA) was adopted to search for the optimal route between different waypoints, and the optimal spanning tree algorithm was used to construct the route network. The experimental results demonstrated that the improved CA could greatly reduce search time and obtain the optimal route while enhancing safety. With the satisfaction of the voyage, the needs of logistics and distribution constraints, a network that had smaller intersection points and redundancy was generated. The models and core ideas proposed in this paper can not only regulate operation of drones but also provide a solid foundation for the distribution of logistics UAV in the future.

Suggested Citation

  • Shan Li & Honghai Zhang & Zhuolun Li & Hao Liu, 2021. "An Air Route Network Planning Model of Logistics UAV Terminal Distribution in Urban Low Altitude Airspace," Sustainability, MDPI, vol. 13(23), pages 1-14, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13079-:d:688195
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    Citations

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    Cited by:

    1. Honghai Zhang & Tian Tian & Ouge Feng & Shixin Wu & Gang Zhong, 2023. "Research on Public Air Route Network Planning of Urban Low-Altitude Logistics Unmanned Aerial Vehicles," Sustainability, MDPI, vol. 15(15), pages 1-17, August.
    2. Zhao Zhang & Chun-Yan Xiao & Zhi-Guo Zhang, 2023. "Analysis and Empirical Study of Factors Influencing Urban Residents’ Acceptance of Routine Drone Deliveries," Sustainability, MDPI, vol. 15(18), pages 1-27, September.
    3. Hu, Zhangchen & Chen, Heng & Lyons, Eric & Solak, Senay & Zink, Michael, 2024. "Towards sustainable UAV operations: Balancing economic optimization with environmental and social considerations in path planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    4. Wenjiao Zai & Junjie Wang & Guohui Li, 2023. "A Drone Scheduling Method for Emergency Power Material Transportation Based on Deep Reinforcement Learning Optimized PSO Algorithm," Sustainability, MDPI, vol. 15(17), pages 1-29, August.
    5. Yi Li & Min Liu & Dandan Jiang, 2022. "Application of Unmanned Aerial Vehicles in Logistics: A Literature Review," Sustainability, MDPI, vol. 14(21), pages 1-18, November.

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