Minimum time control for path tracking problem of intelligent vehicle handling in inverse dynamics

The continuous development of vehicle intelligence and electronic technology has greatly promoted the vigorous development of the automotive industry. The improvement demand of the trajectory tracking, driving safety, and stability of intelligent vehicles has become a hot issue. In order to solve the path tracking problem of vehicle, a high-precision approach for the vehicle path tracking optimization of based on the adaptive sparse collocation method (ASC) is presented. Firstly, a nonlinear 4-DOF vehicle model is established. Then the problem of path tracking with minimum time is transformed into an optimal control problem by the ASC method. Finally, the sequential quadratic programming (SQP) is used to solve the optimal control problem. The simulation results show that the proposed method can solve effectively the problem of vehicle path tracking. And also, the proposed controller can significantly improve the vehicle path tracking performance. It can further improve the path tracking accuracy and lateral stability of vehicles, providing a certain reference for the research on path tracking control of intelligent connected vehicles.