| Title |
UAV Logistics and Distribution Path Planning in Urban Areas Based on Improved PSO and A* Algorithms |
| Authors |
(Lei Li) ; (Huimin Peng) ; (Xingxue Ren) ; (Qianqian Wang) |
| DOI |
https://doi.org/10.5573/IEIESPC.2025.14.2.257 |
| Keywords |
A* Algorithm; Logistics; Optimization algorithm; Particle swarm; Path planning; Unmanned aircraft |
| Abstract |
Drones have shown enormous potential in urban logistics due to their efficiency and flexibility. However, traditional path planning methods such as particle swarm optimization and A* algorithm often find it difficult to meet both efficiency and safety when used alone. Therefore, this study proposes a new unmanned aerial vehicle logistics distribution path planning method. By adjusting parameters and optimizing search strategies, the particle swarm optimization algorithm utilizes the efficient pathfinding ability of A* algorithm to ensure its security. The results show that the obstacle avoidance success rate of the model is 94.85%, which is the best performance compared to other comparative algorithms and provides the shortest and smoothest path selection. This method demonstrates good path planning efficiency and stability, improving logistics and distribution capabilities in urban environments.
This provides valuable reference for intelligent path planning and intelligent transportation systems. |