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Research on Dynamic Risk-Avoidance Route Planning for Multi-drone Collaborative Delivery in Complex Urban Environments

In: AI, Society and Digital Transformation

Author

Listed:
  • Jiang Runxue

    (Nanjing University of Aeronautics and Astronautics, School of Economics and Management)

  • Mi Chuanmin

    (Nanjing University of Aeronautics and Astronautics, School of Economics and Management)

Abstract

To address challenges such as dynamic obstacles, temporary no-fly zones, multi-drone collaborative conflicts, and energy consumption constraints in complex urban environments, a dynamic risk-averse route planning method for multi-drone collaborative delivery is proposed. First, a collaborative delivery model for multi-distribution centers is constructed, integrating a 3D grid-based method to quantify obstacle risks and energy constraints. The urban airspace is stratified into three flight levels, and a dynamic risk update mechanism is designed. Second, a Hybrid A*-Whale Optimization Algorithm (Hybrid A*-WOA) is proposed, combining the improved A* algorithm’s local route search capability with the global optimization characteristics of the Whale Optimization Algorithm. This hybrid approach achieves collaborative optimization of task allocation and dynamic obstacle avoidance for multi-drone systems. Furthermore, a flight-level comprehensive evaluation function is introduced to balance the risk and time cost through weight coefficients and dynamically select the optimal flight altitude.

Suggested Citation

  • Jiang Runxue & Mi Chuanmin, 2026. "Research on Dynamic Risk-Avoidance Route Planning for Multi-drone Collaborative Delivery in Complex Urban Environments," Lecture Notes in Operations Research, in: Xiaolei Xie & Kejia Hu & Guiping Hu & Weiwei Chen & Robin Qiu (ed.), AI, Society and Digital Transformation, pages 39-50, Springer.
    • Handle: RePEc:spr:lnopch:978-3-032-13116-4_4
    DOI: 10.1007/978-3-032-13116-4_4
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