Impaired Driver Assistance Control With Gain-Scheduling Composite Nonlinear Feedback for Vehicle Trajectory Tracking

Abstract

Impaired drivers have deteriorated driving performances that may greatly endanger the road safety. It is challenging to design assistance controllers for the impaired drivers because the impaired driver behaviors are difficult to be modeled and considered in the controller design. To this end, this paper proposes a gain-scheduling composite nonlinear feedback (GCNF) controller to assist the impaired drivers. A driver-vehicle system containing the impaired driver model is developed. The steering behaviors of the impaired drivers are described by deteriorating the driver model parameters and including the driver uncertainties. Based on the driver-vehicle system, a GCNF controller integrating the gain-scheduling technique, the weighted H∞ performance, and the composite nonlinear feedback algorithm is designed to handle the declined driving performances and improve the transient performances. The designed GCNF controller is validated in the carsim simulations. The simulation results show that the GCNF controller can effectively assist the impaired drivers of different impaired levels to reduce the trajectory tracking errors and improve the driving performances.