An Improved Artificial Potential Field Model Considering Vehicle Velocity for Autonomous Driving

Abstract

Path planning is one of the most crucial technologies for autonomous driving. An improved artificial potential field method considering vehicle velocity for path planning is presented in this paper. At first, a combined artificial potential field model is proposed, which includes five components, target potential, road potential, lane potential, vehicle potential and velocity potential. Road potential and lane potential considers the road structure and traffic rules in highway driving. In addition, for vehicle potential, a potential field model is constructed with the absolute velocity and relative velocity which influences the safe distance between the host vehicle and the obstacle vehicle. The design of velocity potential is to prevent unnecessary lane changing behavior. Finally, the collision avoidance path for autonomous driving is calculated with gradient method from the superposition of disparate potential function. According to the simulation experimental validation, the results show the proposed method can achieve good performance for autonomous driving in highway.