Personalized path generation and robust H-infinity output-feedback path following control for automated vehicles considering driving styles

This paper proposes a personalized output-feedback path-following control strategy for automated vehicles. A personalized path generation approach is created to obtain the expected paths of drivers with different driving styles. Historical driving data and road features are used to calculate the waypoints that characterize driving styles. Then, a robust H-infinity output-feedback controller is designed to follow the generated paths. A solution based on matrix partition is provided to compute the output-feedback control gains without using the vehicle lateral velocity signal, which facilitates the practical implementation of the designed controller. The proposed driving strategy is validated in CarSim simulations and scaled car experiments. The results show the personalized paths can match with drivers' driving styles and can be tracked by the designed output-feedback path-following controller.