Path Preview Tracking for Autonomous Vehicles Based on Model Predictive Control

Abstract

For the autonomous vehicles path tracking problem, a preview tracking strategy is proposed based on model predictive control (MPC) in this paper. First, under the scenario that the road ahead information is available, an augmented error system is constructed based on the prediction tracking error, state difference and preview information. By introducing an appropriate objective function, the original path preview tracking problem is transformed into an optimization problem of the unconstrained predictive control. Second, the optimal prediction control sequence is obtained according to the minimum value principle, and its first component, which contains the non-causal tracking error, state feedback and preview feedforward, is utilized to perform the receding-horizon control. Furthermore, the optimization problem of the constrained predictive control is also considered. Finally, the platform of CarSim and Simulink is adopted to verify the effectiveness of the path preview tracking.