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

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.

Automated summary

This study proposes an intelligent vehicle human-machine cooperative control method by constructing a driver model and setting a penalty factor to adapt to the varying previewing characteristics of a human. A steering torque controller is designed using gain-scheduling control to effectively alleviate conflicts between the driver and the intelligent driving system.