Urban Air Mobility and Unmanned Aerial Vehicle Path Planning in Dynamic Urban Environments: A Review

The complexity of three-dimensional (3D) dynamic urban environments poses new challenges to emerging unmanned aerial vehicle (UAV) path planning, especially in dense buildings, dynamic obstacles, and multi-UAV collaboration. This paper reviews mainstream 3D path planning algorithms (including RRT, PRM, the ant colony algorithm, the artificial potential field method, and A*) and analyzes their core principles, applicable scenarios, advantages, and disadvantages. The study finds that each algorithm has its disadvantages: RRT lacks optimality, PRM has high computational cost, the ant colony algorithm is poor in real-time performance, APF is prone to local optima, and A* performs well in static environments. Future research should explore hybrid strategies combining multiple algorithms to improve adaptability in dynamic complex environments, providing efficient solutions for urban low-altitude UAV operations.