Volume 26 Issue 2
Feb.  2026
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FENG Di-kun, ZHANG Hong-hai, HUA Ming-zhuang, DI Juan, SHAN Yi-xuan. Multi-layer heterogeneous take-off and landing site network collaborative planning for urban low-altitude logistics[J]. Journal of Traffic and Transportation Engineering, 2026, 26(2): 110-124. doi: 10.19818/j.cnki.1671-1637.2026.086
Citation: FENG Di-kun, ZHANG Hong-hai, HUA Ming-zhuang, DI Juan, SHAN Yi-xuan. Multi-layer heterogeneous take-off and landing site network collaborative planning for urban low-altitude logistics[J]. Journal of Traffic and Transportation Engineering, 2026, 26(2): 110-124. doi: 10.19818/j.cnki.1671-1637.2026.086
shu

Multi-layer heterogeneous take-off and landing site network collaborative planning for urban low-altitude logistics

doi: 10.19818/j.cnki.1671-1637.2026.086
  • 1.

    College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China

  • 2.

    College of General Aviation and Flight, Nanjing University of Aeronautics and Astronautics, Liyang 213300, Jiangsu, China

  • 3.

    College of Airport Management, Shanghai Civil Aviation College, Shanghai 201300, China

Funds:

Major Project of National Social Science Foundation of China 22&ZD169

Key Project of the Joint Fund for Civil Aviation National Natural Science Foundation of China U2133207

Key Project of the Joint Fund for Civil Aviation National Natural Science Foundation of China U2333214

Inter-disciplinary Innovation Fund for Doctoral Students of Nanjing University of Aeronautics and Astronautics KXKCXJJ202405

More Information
  • Corresponding author: ZHANG Hong-hai, professor, PhD, E-mail: honghaizhang@nuaa.edu.cn
  • Received Date: 2025-06-05
  • Accepted Date: 2025-11-27
  • Rev Recd Date: 2025-10-29
  • Publish Date: 2026-02-28
    Abstract
  • To achieve effective planning and safe operation of take-off and landing site networks for low-altitude logistics, the collaborative planning of multi-layer take-off and landing site networks for unmanned aerial vehicle (UAV) logistics in urban environments was investigated. By considering realistic factors such as UAV performance constraints and airspace restrictions and combining a three-layer distribution system of "vertihub-vertiport-terminal", a three-layer network collaborative planning model for take-off and landing sites was built to achieve minimum transportation cost, minimum construction quantity and maximum network fairness. A customized continuous optimization framework was designed to quickly realize the generation of initial solutions, solution of discrete variables and local optimization of continuous variables. The effectiveness of the collaborative planning model and the combined algorithm was validated based on logistics data from Shanghai. The results show that the proposed collaborative planning model can effectively realize the location layout of the take-off and landing site network. The designed HLO (Human Learning-based Optimization) algorithm performs better than optimization algorithms including GA (Genetic Algorithm) and NSGA-Ⅱ (Non-dominated Sorting Genetic Algorithm Ⅱ). Significance tests indicate that the SA-based local optimization algorithm can stably improve transportation cost by approximately 2.15%, effectively enhancing the optimality of planning results. Sensitivity analysis reveals that the weight design and step factor significantly affect the solution effect of the model. The weight of the total number of vertihubs and vertiports should not be less than 0.5, and the optimal step factor is between 0.05 and 0.06. The weight configuration for the number of vertihubs and vertiports notably affects the number of vertiports. The number of vertiports continuously increases with its weight, while the optimal number of vertihubs remains unchanged. The research can provide decision-making reference for network planning and collaborative operation of take-off and landing sites in urban low-altitude logistics.

     

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