Steering control strategy guide by two preview vision cues

Abstract

Vision cues play an important role in states feedback in motion control. However, the existing driver steering models consider little about vision cues utilized by human drivers during their steering procedure. This paper presents a novel steering control strategy based on two preview points (far point and near point). The far point is used to compensate the steering wheel by predicting the upcoming curvature change with respect to the lane, while the near point as vision feedback, which is used to tune the steering wheel by estimating the errors of vehicle states and lane center. To obtain much smoother lateral acceleration during steering, a forward internal model is established using a second-order yaw dynamics system that captures the influence of yaw angular acceleration caused by steering wheel angle. The input parameter of the second-order system is the vision cues of both the near and far points, and the output parameters are the ideal yaw angle and yaw rate. To calculate suitable the steering wheel angle, an adaptive controller is designed using fuzzy sliding technology, which is used as the input of the vehicle system dynamics. Numerical simulation results show that the proposed method performs better than the existing driver steering models in case of imitating human drivers’ behavior, and exhibits excellent adaption to the lane curvature change.