Automatic driving path planning based on A-Star algorithm

Path planning is one of the important contents of autonomous driving system research, the core of which is to accurately and rapidly search the optimal path between the starting point and the end point. A-Star algorithm is A path - finding algorithm which uses heuristic information to improve search efficiency. In this paper, the path planning of automatic driving is realized based on the A-Star algorithm, and the lateral control strategy is replaced by the traditional pure tracking method with Stanley track tracking method to optimize the control scheme, further meeting the requirements of real-time, high efficiency and accuracy of the decision control system. The automatic driving system was built in PreScan and Simulink co-simulation environment to explore the efficiency of the path planning algorithm and the control ability of the trajectory tracking algorithm. The error between the path trajectory and the target ideal path under the control of the algorithm is compared and analyzed in the simulation environment to prove the feasibility and effectiveness of the algorithm. Finally, the algorithm is deployed on the autonomous driving vehicle platform to verify that it can meet the requirements of autonomous driving of small unmanned vehicles.