摘要
为提升消防车路径规划效率,验证蚁群算法在民航机场动态场景中的适用性与优化能力,本文以某机场为例,构建栅格化机场地图,嵌入跑道、滑行道、建筑物等障碍物,设置单/多消防车起点与随机着火点的3类典型场景,设计融合距离、安全性与可行性的启发式因子,基于Python实现蚁群算法,通过迭代寻优求解最短救援路径。结果表明:3种典型场景中,算法均能快速收敛至最优路径,验证了算法的稳定性与鲁棒性。蚁群算法可有效应对机场复杂布局与突发障碍,显著提升消防响应速度。
In order to improve the efficiency of fire truck path planning and verify the applicability and optimization ability of ant colony algorithm in the dynamic scene of civil aviation airport,this study selects a representative airport as a case study.A gridded airport map was constructed,incorporating obstacles such as runways,taxiways and buildings were embedded.Three typical scenarios are designed,including single/multiple fire truck starting points and random fire locations.Heuristic factors integrating distance,safety and feasibility were introduced to optimize path planning.,The ant colony algorithm is implemented using Python,and the shortest rescue path is derived through iterative optimization..The results demonstrated that the proposed algorithm consistently converged to the optimal path across three typical scenarios,confirming its stability and robustness.Furthermore,the ant colony optimization algorithm effectively handled complex airport layouts and dynamically introduced obstacles,significantly enhancing emergency response efficiency in firefighting operations.
作者
张明格
智茂永
周梓晨
孙强
侯政佐
ZHANG Mingge;ZHI Maoyong;ZHOU Zichen;SUN Qiang;HOU Zhengzuo(College of Civil Aviation Safety Engineering,Civil Aviation Flight University of China,Deyang Sichuan 618307,China;Civil Aircraft Fire Science and Safety Engineering Key Laboratory of Sichuan Province,Deyang Sichuan 618307,China)
出处
《安全》
2025年第8期27-34,共8页
Safety & Security
基金
中国民航局民航安全能力建设项目(MHAQ2024035)。
关键词
蚁群算法
路径规划
机场
消防救援
ant colony algorithm
path planning
airport
fire rescue
