Path Planning Algorithms for Self-Driving vehicle based on improved RRT-Connect

This study aims to solve path planning of intelligent vehicles in self-driving. In this study, an improved path planning method combining constraints of environment and vehicle is proposed. The algorithm designs a reasonable path cost function, then uses heuristic guided search strategy to improve the speed and quality of path planning, and finally generates smooth and continuous curvature paths based on the path post-processing method based on the requirements of path smoothness. simulation test show that compared with the basic RRT, RRT-connect and RRT* algorithms, the path length of the proposed algorithm can be reduced by 19.7%, 29.3% and 1% respectively and the maximum planned path curvature of the proposed algorithm is 0.0796 m-1 and 0.1512 m-1 respectively under the condition of a small amount of planning time. The algorithm can plan the more suitable driving path for intelligent vehicle in complex environment.