Research on the Steering Torque Control for Intelligent Vehicles Co-Driving With the Penalty Factor of Human–Machine Intervention

Abstract

In intelligent vehicle cooperative systems, the mismatch in driving characteristics between a human and a machine and the driver misoperation caused by this mismatch result in human–machine conflicts, which significantly affect driving safety. Therefore, an intelligent vehicle human–machine cooperative steering torque control method is proposed herein. To adapt the intelligent system to the varying previewing characteristics of a human, a time-varying previewing driver model is constructed, and a penalty factor for human–machine intervention is designed based on fuzzy rules to assign driving control rights by assessing the driver’s state. Consequently, a human–vehicle–road model with driver preview time and penalty factor as varying parameters is established. Based on gain-scheduling control, a human–machine cooperative steering torque controller is designed to adapt to the varying previewing characteristics of a human and the change in human–machine intervention. The stability and robustness of the entire parameter space are guaranteed by constraining the poles in a certain region. Finally, the proposed human–machine cooperative control scheme demonstrates the effective alleviation of conflicts between the driver and the intelligent driving system.