Design and Control of Personalized Steering Feel for Steer-by-Wire Systems

The realization of personalized steering feel plays a crucial role in prompting the widespread adoption and driver acceptance of autonomous vehicles (AVs). Since human drivers have distinctly different steering feel preferences and requirements, the personalized matching is essential for ensuring safety and comfort of human-vehicle collaboration. Therefore, this paper proposed a novel personalized steering feel design method based on the driver’s steering characteristics, utilizing steer-by-wire (SBW) vehicle as the platform. Specifically, the personalized steering feel was composed of conventional steering torque, customizable module and mechanical compensation. The conventional steering torque was calculated by a tire model. Then, the concept of road sense style was the first introduced as the basis for the design of the customizable module. Furthermore, a complete road sense style recognition system was put forward from the perspective of semi-supervised learning. The driver’s steering characteristics were collected and classified by k-means algorithm, and a generic road sense style recognition model was built and optimized through support vector machine with crow search (CS-SVM) method. The recognition results were integrated into the design of the personalized steering feel. In addition, a steering controller adopting sliding mode control (SMC) was designed to facilitate stable and rational steering maneuvers by drivers. Finally, driving experiments were performed. The results show that the designed steering feel can rapidly adapt to diverse drivers’ preferences, offering a more satisfying driving experience and improving overall safety.