Model predictive control for lane keeping system in autonomous vehicle

Abstract

This paper presents a controller for lane keeping system (LKS), and the method of the reference trajectory generation is interpolating five preview points obtained by sensors. Its mean purpose is to reduce the demand for sensors by only using five points. Also the distance between these five preview points is determined by the longitudinal velocity. The computation of the controller has been achieved by casting the model predictive control (MPC) for tracking problem into the quadratic programming (QP) problem. The steering angle is minimized to generate the optimal control sequence and the effectiveness and robustness of the proposed approaches are demonstrated through co-simulations of Matlab/Simulink and CarSim under the different velocity. And the simulation results show that the MPC controller is suitable for reducing the lateral displacement and achieving better performance.