Research on autonomous vehicle path tracking control considering roll stability
Fen Lin, Shaobo Wang, Youqun Zhao, Yizhang Cai
Abstract
For autonomous vehicle path tracking control, the general path tracking controllers usually only consider vehicle dynamics’ constraints, without taking vehicle stability evaluation index into account. In this paper, a linear three-degree-of-freedom vehicle dynamics model is used as a predictive model. A comprehensive control method combining Model Predictive Control and Fuzzy proportional–integral–derivative control is proposed. Model Predictive Control is used to control the vehicle yaw stability and track the target path by considering the front wheel angle, sideslip angle, tire slip angles, and yaw rate during the path tracking. Fuzzy proportional–integral–derivative algorithm is adopted to maintain the vehicle roll stability by controlling the braking force of each tire. Co-simulation with CarSim and MATLAB/Simulink shows the designed controller has good tracking performance. The controller is smooth and effective and ensures handling stability in tracking the target path.