Research on automatic obstacle avoidance algorithm for intelligent networked vehicles
Yingying Li, Fuzheng Wang, Jinmei Li, Fei Liang, Xiang Pan · 2023
This paper proposes an optimised artificial potential field obstacle avoidance algorithm, which constructs an on-board model for automatic obstacle avoidance based on biological intelligence and physical phenomena, and uses multiple parametric estimates of car orientation information and car-obstacle distance parameters to perform obstacle avoidance control in three steps: detecting the obstacle, developing an adjustment plan, and returning to the normal route. The experimental data show that the intelligent optimisation algorithm outperforms the conventional algorithm in terms of distance to obstacles, algorithm computation time, and path planning time.