Design of Intelligent and Connected Vehicle Path Tracking Controller Based on Model Predictive Control

Abstract

In order to solve the problem of autonomous steering of intelligent vehicles and to improve the steering precision and stability during the high-speed movement, and considering the path tracking control, a path tracking control method of variable parameters under the background of intelligent and connected vehicle is proposed. A path tracking controller for intelligent vehicle based on the model predictive control principle is designed. Firstly, a 3-degree-of-freedom dynamic model is considered as the control system. Secondly, a quadratic form cost function of the system is determined after linearizing the system, and the form of the constraints are determined according to the cost function. Thirdly, the controller's parameters for typical operation conditions are obtained with the off-line simulation of the Carsim and Matlab/Simulink platforms. Finally, the intelligent and connected vehicle can complete the automatic steering by selecting the appropriate path tracking control parameters according to the road type where the vehicle is actually located and the actual speed of the vehicle. The simulation results show that the controller has a better control effect than the controller with fixed parameters. This controller can achieve higher tracking accuracy and driving stability when the vehicle is moving at high speed.