Research on parallel parking path planning and tracking control of unmanned vehicles

Aiming at the problems of discontinuous curvature of the planned path, difficulty in finding the optimal reference path and high control accuracy requirements in tracking control for unmanned vehicles in the process of parallel parking, an optimal reference path planning method based on arc line and multi-objective optimization function and a path tracking control strategy based on nonlinear model predictive control are proposed. Firstly, the upper and lower boundaries of the exercisable area are obtained by the tangent of the arc and the straight line, and the multi-objective optimization function is designed to obtain the optimal arc-line combination, and the optimal reference path is obtained by polynomial curve fitting. Secondly, a path-following controller is designed using nonlinear model predictive control. Finally, a comparative analysis is carried out in MATLAB/Simulink and Carsim with the controller based on pure tracking design. The results show that the optimal reference path curvature obtained by the proposed method is continuous without sudden change, and the designed tracking controller has better tracking accuracy.