Path tracking and adaptive cruise control considering vehicle mass and road gradient

Abstract

For driver safety and convenience, research on autonomous driving is being actively conducted. In real driving, there exist mass uncertainty from passenger or load and the road has various road gradient. For real driving situations especially when deceleration is needed, accurate mass and road gradient information are essential and directly related to safety problems. In this study, path tracking and adaptive cruise control considering vehicle mass and road gradient are designed. Model Predictive Control(MPC) is designed for path tracking and adaptive cruise control while considering lateral and longitudinal vehicular systems. Vehicle mass and road gradient are estimated by Recursive Least Square(RLS) with multiple forgetting factors and applied to the MPC for improving the accuracy of the model and ultimately the performance of MPC. The real-time simulation was conducted before and after estimation and the improvement of the safety was verified.