Autonomous Parking Path Tracking Control Based on Interference Suppression

Owing to the increased demand for autonomous driving and advanced driver assistant systems, autonomous parking configurations have been widely researched. In order to solve the problem of path tracking accuracy degradation, caused by ignoring the external interference in the actual parking process and the uncertainty of vehicle steering modeling, a parking path tracking algorithm, combining Sliding Model Control (SMC) and Extended State Observer (ESO), is proposed. First, the vehicle kinematics model is established, which includes many external interference factors, such as lateral position, speed, heading angle, uncertainty parameters and time delay of steering mechanism. Considering the vehicle physical constraints and boundary condition constraints, during the parking process, the parking reference path is designed according to reverse outbound driving, while the parking collision analysis and path smoothing are further carried out. Next, an ESO is designed to observe and compensate the external disturbances and model uncertainties, treating these as the total disturbances of the system. On this basis, a SMC for parallel parking path tracking is designed. The observed value of ESO is used as the compensation in the SMC, to weaken the influence of external interference. Finally, using Matlab simulation, the feasibility and effectiveness of the proposed path planning and tracking control method are verified. The simulation results show that, the maximum tracking error of lateral position is less than 0.01m, whereas the maximum tracking error of heading angle is less than 2.5°. Comparing two control strategies, the control effect of the designed SMC with ESO is better than that of the traditional SMC controller, while the ability of resisting external interference is stronger. In addition, real vehicle tests are carried out, to verify the effectiveness of the proposed control method. The test results show that, the vehicle can safely park in the parking space, quickly and accurately, even if there is external interference. The proposed method can produce the parking trajectory according to the given constraints and control the vehicle to complete the parking operation accurately along the planned path.