Intelligent Vehicle Path Tracking Control Based on Model Predictive Control

With the rapid development of intelligent transportation system, the path tracking control of intelligent vehicles has become one of the key technologies. In this paper, the path tracking method of intelligent vehicles based on model predictive control (MPC) is studied deeply. Firstly, the control law for adaptive adjustment of the optimal time domain is designed based on the two-degree-of-freedom vehicle dynamics model and the model control algorithm. Next, the MPC trajectory tracking controller is built based on the error characteristics of the actual front wheel angle and the predicted front wheel angle. Finally, the results of Matlab/Simulink and Carsim joint simulation show that the MPC has significant advantages compared with the traditional PID controller in terms of path tracking accuracy, stability, and adaptability to complex road conditions, etc., which provides theoretical support for the further optimization of the path tracking technology of intelligent vehicles.