Technical Paper
Data-Enabled Human-Machine Cooperative Driving Decoupled from Precise Driver Steering Characteristics and Vehicle Dynamics.
2024-04-09
2024-01-2333
Human driving behavior's inherent variability, randomness, individual differences, and dynamic vehicle-road situations give human-machine cooperative (HMC) driving considerable uncertainty, which affects the applicability and effectiveness of HMC control in complex scenes. In order to overcome this challenge, we present a novel data-enabled game output regulation approach for HMC driving. Firstly, a global driver-vehicle-road (DVR) model is established considering the distinct driver's steering characteristic parameters, such as delay time, preview time, and steering gain, as well as the uncertainty of tire cornering stiffness and variable road curvature disturbance. The robust output regulation theory has been employed to ensure the global DVR system's closed-loop stability, asymptotic tracking, and disturbance rejection, even with an unknown driver's internal state. Secondly, an interactive shared steering controller has been designed to provide personalized driving assistance.