针对城市场景下载人电动垂直起降飞行器（electric vertical takeoff and landing, eVTOL）路径规划问题进行了研究。首先，使用危险度栅格法进行三维城市空间建模，对选定型号的eVTOL飞行器，以航程、运行风险和高度变化为目标函数，结合飞行器自身特性及环境限制，构建了多约束条件的载人eVTOL路径规划模型。然后，设计了一种改进人工电场算法（improved artificial electric field algorithm, IAEFA），在传统人工电场算法（artificial electric field algorithm, AEFA）的基础上增加了自适应库伦参数，并在库伦常数的计算中引入递减系数，以此进行仿真求解。实验结果显示，所构建的模型可以达到预期效果。使用改进算法进行路径规划的求解效果更优，相较传统粒子群算法和人工电场法，航程更短，高度变化更小且运行更为安全。最后，根据对照实验确定递减系数的取值，当递减系数取值为1.5时，改进算法的求解效果最优。

The path planning problem of electric vertical takeoff and landing (eVTOL) aircraft in urban scenarios was studied. Firstly, a three-dimensional urban space model was constructed using the hazard grid method. Considering the selected model of eVTOL, with range, operational risk, and altitude variation as objective functions, a path planning model for manned eVTOL with multiple constraints was developed, taking into account the characteristics of the aircraft and environmental limitations. Subsequently, an improved artificial electric field algorithm (IAEFA) was proposed, which enhances the traditional artificial electric field algorithm(AEFA) by introducing an adaptive Coulomb parameter and incorporating a decreasing coefficient in the Coulomb constant calculation for simulation-based solution. Experimental results demonstrate that the constructed model achieves the expected outcomes. The solution effectiveness of path planning using the improved algorithm surpasses that of traditional particle swarm optimization and artificial electric field methods, resulting in shorter range, minimal altitude variation, and enhanced safety during operations. Finally, based on comparative experiments, the value of the decreasing coefficient was determined. The optimal solution effectiveness of the improved algorithm is achieved when the decreasing coefficient is set to 1.5.