Research on automatic driving control strategy based on improved model predictive control

Abstract

Abstract As a new technology direction in the automotive industry in recent years, automatic driving technology has played an important role in reducing traffic accidents, promoting energy conservation and emission reduction, and improving the efficiency of high-speed and urban roads. As one of the key technologies of autonomous vehicles, the performance of control algorithm greatly affects the smoothness of vehicle driving and the accuracy of track tracking. In order to consider the lateral control and longitudinal control accuracy at the same time, and ensure that the vehicle travels according to the given trajectory, this paper first establishes the vehicle kinematics model, and improves the traditional model predictive control algorithm, which realizes the high dynamic control of the desired trajectory while ensuring the vehicle stability and comfort. Finally, based on the built real vehicle test platform for automatic driving, the acceleration and deceleration test and the high-speed serpentine test are designed. By analyzing the test data, it can be seen that the control algorithm proposed in this paper can effectively achieve the vehicle trajectory tracking, and the control accuracy is improved.