Autonomous Parking Path Planning Method for Intelligent Vehicles Based on Improved RRT Algorithm

Abstract

Autonomous valet parking technology refers to a vehicle’s use of onboard sensors and line-controlled chassis to carry out a fully automatic valet parking function, which can greatly improve the driver’s experience. This study focuses on autonomous parking, employing environmental modeling and vehicle kinematics models. Innovatively applying the PSBi-RRT algorithm to path planning in autonomous parking systems constitutes this research’s contribution to this field. Firstly, the environment is modelled by the raster method; then, the PSBi-RRT algorithm is used for path planning, and a B-spline curve is used for path optimization. Speed and acceleration are smoothed at the same time, and finally, a smooth and obstacle-avoiding path planning scheme is obtained. The results show that an autonomous parking system based on the PSBi-RRT algorithm performs path planning from the vehicle to the parking space. Compared to RRT and Bi-RRT, PSBi-RRT generates shorter planning paths, smoother heading angle changes, shorter planning times, fewer nodes, and higher success rates. This research provides theoretical support for the development of autonomous parking technology.