Research on Automatic Lane Change Path Planning Based on Improved Rapidly-Exploring Random Trees

In order to solve the problem of automatic lane change in straight road environment, a Segment-orienting rapidly-exploring random trees algorithm (SO-RRT) is designed based on the idea of Fast-biasing RRT algorithm and piecewise design. Firstly, the local map is preprocessed, and then the control points are obtained by geometric analysis of the map according to the obstacle vehicle around the vehicle and the speed of the vehicle. On this basis, the Fast-bias RRT is carried out in segments, and the obtained path is optimized and fitted. After processing, the planned path is finally obtained, which ensures that the planned path meets the kinematic constraints of the vehicle and is as close as possible to the optimal solution. CarSim was used for vehicle and road modeling and co-simulation with Matlab / Simulink. The path planning was carried out in Simulink and the hybrid algorithm combining model predictive control algorithm and PID algorithm was used to realize path tracking. The simulation results show that the path planning and tracking can be well realized under the conditions of 60 km/h and 80 km/h, which verifies the effectiveness of the automatic lane change auxiliary system.