An Improved Lateral Vehicle Control Design Using Ultra-Local Model-Based Slip Estimation

In the paper, a complex estimation and control algorithm is presented for autonomous vehicles. The algorithm has an observer layer that aims to estimate the slip of the vehicle on both the front and rear axles. The observer design is based on the combination of the Linear Parameter Varying (LPV) approach and the ultra-local model technique. The goal of the ultra-local model is to update the cornering stiffness in order for the lateral dynamics of the vehicle model to be updated. A Model Predictive Control (MPC) is developed based on the updated model and the estimated slips, that can maintain the lateral stability of the vehicle even under extreme circumstances, e.g., moving on a surface with a low adhesion coefficient. This stabilization is achieved by limiting the slips of the vehicle. The proposed algorithm is tested through a complex test scenario using a high-fidelity simulation software, CarMaker.