Research on control algorithm of a automatic driving robot based on improved model predictive control

Abstract

Abstract The automatic driving robot can replace the driver in the traditional test and ADAS test; Model Predictive Control (MPC) is used in the horizontal and vertical control process of high-speed driving. According to the uncertainties and complex constraints of automatic driving horizontal and vertical control, the adaptive improvement of MPC is proposed, which can better adapt to the characteristics of self driving vehicles, sensors and tyres. This paper proposes a multi-layer and multi time automatic driving control strategy based on improved MPC. Visual studio is used to write the upper computer software of the automatic driving robot, which realizes good human-computer interaction. The automatic driving robot is verified in real vehicle test. The experimental results show that the transverse and longitudinal control strategy of the improved model predictive control is stable, and the automatic driving robot can realize the high precision and high dynamic control of vehicle steering, pedal and shift.