Journal of Systems & Management ›› 2025, Vol. 34 ›› Issue (5): 1305-1315.DOI: 10.3969/j.issn.2097-4558.2025.05.009

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Joint Air-Ground Route Planning of Searching and Rescue During Flood Disaster

LÜ Ying,LI Yue,SUN Huijun   

  1. School of Systems Science, Beijing Jiaotong University, Beijing 100044, China
  • Received:2023-01-16 Revised:2024-04-21 Online:2025-09-28 Published:2025-10-16

洪涝灾害场景下空地联合的搜救路径规划

吕莹,李悦,孙会君   

  1. 北京交通大学 系统科学学院,北京  100044
  • 基金资助:
    国家自然科学基金资助项目(72471026,72288101,72091513)

Abstract: To address the difficulties in obtaining information about environment and road network in the rescue area in flood disaster, unmanned aerial vehicles (UAVs) are applied to the post-disaster survey work, and a research framework for the path planning system of air-ground joint is proposed for the whole rescue process, involving three stages: UAVs searching, image processing, and disaster rescue. The path planning problem of UAVs is abstracted into a complete coverage path planning model, and the region segmentation-path planning algorithm considering energy consumption is used to solve the problem. Then, through the image processing module, the information of road network and personnel location in the disaster area is extracted. The rescue path problem in disaster area is set up as a capacitated vehicle route planning model and solved by particle swarm optimization. The example shows that the planning algorithm of UAVs can reduce the energy consumption by 14.9%, and the average utilization rate of rescue tools obtained by the path planning algorithm reaches 92.5%. Finally, the effects of different capacities of rescue tools on rescue time and cost are quantitatively analyzed, and suggestions on the use of rescue tools are given in different rescue scenarios.

Key words: post-disaster relief, unmanned aerial vehicles (UAVs), path planning

摘要: 针对洪涝灾害后救援区域环境信息与路网数据难于获取的问题,本研究将无人机应用于灾后勘察工作,提出面向救援全过程的空地联合的路径规划系统框架,涵盖无人机勘察、图像处理和灾区救援3个阶段。首先,将无人机路径问题抽象为全覆盖路径规划模型,采用考虑能耗的区域分割与路径规划算法进行求解;其次,通过图像处理模块提取灾区路网及受灾人员位置信息;最后,将救援任务建模为带容量约束的车辆路径规划问题,并应用粒子群优化算法求解。仿真结果表明,所提出的无人机规划算法可降低14.9%的能耗,救援路径规划算法所得的救援工具的平均利用率达到92.5%。通过定量分析不同救援工具容量对救援时间与成本的影响,本研究针对不同救援场景提出了救援工具的使用建议。

关键词: 灾后救援, 无人驾驶飞机, 路径规划

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