Research on Active Obstacle Avoidance of Intelligent Vehicles Based on Improved Artificial Potential Field Method

In the study of autonomous obstacle avoidance intelligent vehicles, traditional artificial potential field method has problem that vehicle may fall into local minima and lead to failure. Therefore, this paper improves function. Based on dynamics model, a strategy jumping out based smaller steering angles is proposed. By finding angle setting suitable jump step length, enabled minima. Simulation experiments by MATLAB show improved can comparing planned trajectories in static dynamic obstacles situations, trajectory smooth curvature smaller. The tracked Carsim platform, test results reduces front wheel while satisfies constraints during active avoidance, which verifies stability rationality method.