Intelligent Vehicle for Collision Avoidance Using Artificial Potential Field with Speed Variation

Abstract

In this paper, we present a novel approach for waypoint tracking scheme with a local path planner based on the artificial potential field (APF) to avoid dynamic obstacles. It is reported that APF is highly efficient in collision-avoidance issues, but there is less work combining the waypoint tracking with APF-based local path planner. To enrich this field, a waypoint tracking using APF with speed variation is proposed to prevent the possibly excessive tire slip angle when the vehicle is driven at a high speed. The simulation results show that the proposed algorithm is effective in collision avoidance with dynamic obstacles, especially for waypoint tracking scenario. The proposed system framework is validated with the vehicle dynamic lateral motion model in MATLAB/Simulink and CarSim.