Abstract
Abstract In this paper, a path tracking algorithm of adaptive trajectory prediction is presented. To begin with, trajectory prediction equations were built from two degree of freedom vehicle dynamics model. Based on the assumption that the yaw rate of a vehicle does not change in a control period, the trajectory prediction equations are solved to obtain the vehicle’s target front wheel steering angle. By comparing the curves of trajectory, tracking error, and yaw angle of the vehicle, this paper analyzes the effect of control period on tracking accuracy and vehicle stability. Based on this, a path tracking algorithm of adaptive control period was designed using fuzzy control, adaptively adjusting control period according to lateral deviation and yaw rate. From the simulation analysis, it can be seen that optimized path tracking algorithm can satisfy the need for vehicle tracking under low speed, and the problem of vehicle runaway under high speed is overcome to a certain extent. The vehicle’s path tracking performance is significantly improved.
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