Research on the Design and Comparison of Trajectory Tracking Controllers for Automatic Parking System

As one of the essential parts of automatic parking system (APS), the parking motion control module directly affects the system performance and driver experience. Therefore, it is necessary to design a simple, robust and efficient trajectory tracking algorithm which adapt to the various parking conditions. Firstly, considering the predictability and the ability of dealing with various system constraints, the model predictive control (MPC) lateral controller is designed. Then, the second lateral controller based on linear quadratic regulator (LQR) algorithm is designed, which has the excellent capability of balancing the multiple performances of the system. Finally, Stanley lateral controller is designed as the benchmark for horizontal comparison. Parallel and vertical parking simulation environments are proposed to verify the effectiveness of the designed lateral controllers, and the advantages and shortcomings of each control algorithm are horizontally analyzed and summarized. It can be concluded that MPC lateral controller performs well in each parking simulations, which shows a great potential in the future. LQR lateral controller has a good result in the parallel parking simulation, but shows poor performance in the vertical parking simulation due to ignoring the disturbance of the trajectory curvature. In low-speed parking environments, Stanley lateral controller also performs well but it ignores the vehicle dynamics.