1673-159X

CN 51-1686/N

面向城市空中交通的eVTOL飞行器路径规划算法对比

A Comparative of eVTOL Aircraft Path Planning Algorithms for Urban Air Mobility

  • 摘要: 随着城市空中交通(UAM)迅速发展,为实现eVTOL飞行器在城市低空空域高效安全运行,解决其路径规划面临的空域复杂多变、障碍物繁杂、低空飞行、噪声和气象等问题,从而推动城市空中出行时代的快速到来,文章引入AirMatrix空域规划概念作为城市低空空域规划方案,并针对eVTOL的城市低空运行特点对AirMatrix空域作了四维区块化分割,结合这一空域规划方案,选取了快速搜索随机树(RRT)算法、改进A*算法和粒子群算法(PSO)算法进行了综合分析和三维地形中的仿真验证,其结果表明:RRT算法搜索速率最快; 改进A*算法具有最好的路径规划质量;PSO算法在路径规划长度和搜索速度两方面均有所欠缺。改进A*算法相对RRT算法和PSO算法更适用于低密度城市空域路径规划。

     

    Abstract: This paper introduces the AirMatrix airspace planning concept as an urban low-altitude airspace planning scheme to realize the efficient and safe operation of eVTOL aircraft in urban low altitude airspace, and to solve the problems of complex and variable airspace, complicated obstacles, low altitude flight, noise and meteorology faced by its path planning, thus promoting the rapid arrival of urban air mobility era. The AirMatrix airspace is divided into four-dimensional blocks according to the urban low-altitude operation characteristics of eVTOL. In this paper, the rapidly-exploring random trees (RRT) algorithm, the improved A* algorithm, and the particle swarm optimization (PSO) algorithm are selected to perform a comprehensive analysis and simulation verification in 3D terrain. The results show that the RRT algorithm has the fastest search rate, the A* algorithm has the best path planning quality, and the PSO algorithm is lacking in both path planning length and search rate. Therefore, the A* algorithm is considered to be more suitable for low-density urban airspace path planning than the RRT and PSO algorithms.

     

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