Local Path Planning of Autonomous Vehicles Based on A* Algorithm with Equal-Step Sampling
Yijing Wang, Zhengxuan Liu, ZUO Zhiqiang, Ll Zheng · 2018
Path planning is an important component in the study of autonomous vehicles. And local path planning is a pivotal issue, which will greatly influence the safety and comfort of the vehicle. On the premise of security, this paper proposes a novel A* algorithm with equal-step sampling based on vehicle kinematics model to improve the comfort of the path as much as possible. The algorithm is based on vehicle kinematics and introduces an enhanced cost function. The simulation results illustrate the feasibility of this approach on lane-keep and obstacle avoidance in different scenarios. In addition, the real vehicle test results of “Smart Driving” autonomous vehicle of Tianjin University demonstrate the capability of real-time implementation.