Personalized design strategy of vehicle steer-by-wire characteristics considering driving style

Abstract

In order to meet the needs of drivers with different driving styles and improve driving comfort and safety, a personalized design strategy of vehicle steer-by-wire (SBW) characteristics considering driving style is proposed in this paper. Firstly, based on the driver hardware-in-the-loop test bench, the driver’s driving characteristic data is collected under double lane change condition. Then, the K-means clustering algorithm is adopted to classify the driver’s driving style into cautious type, general type and radical type. Based on this, combined with the clustering results and grid search method, the support vector machine algorithm is used to construct the driving style identification model. Finally, considering the driving style, vehicle stability and steering wheel alignment characteristics, the driver personalized variable steering ratio strategy is designed based on the ideal transmission characteristics, and the personalized SBW performance is analyzed under step condition and sinusoidal condition. The results indicate that the proposed personalized design strategy of vehicle SBW characteristics considering driving style can not only accurately identify driving style, but also meet the needs of drivers with different driving styles for vehicle response.