Addressing the issue of increased tracking deviation due to higher vehicle speeds,a path tracking algorithm based on an improved Stanley controller was studied.Firstly,utilizing a two-degree-of-freedom vehicle kinematic model,the gain parameters of the Stanley controller were adjusted using a fuzzy controller with lateral deviation and heading deviation as input,thereby enhancing the path tracking accuracy.Secondly,the effectiveness of the improved Stanley controller was validated through joint simulation using MATLAB/Simulink and CarSim.Simulation results demonstrate that the algorithm can adjust the parameters of the Stanley controller based on the vehicle's operating state,effectively reducing lateral error,the maximum lateral error for straight path tracking can be reduced to 0.11m,while for double lane change path tracking,it can be reduced to 0.12 m.
Stanley controlfuzzy algorithmpath trackingCarSim/Simulink
万方数据
维普
