Study on Steering Angle Input during the Automated Lane Change of Electric Vehicle

The trajectory planning and the accurate path tracking are the two key technologies to realize the intelligent driving. The research of the steering wheel angle plays an important role in the path tracking. The purpose of this study is to optimize the steering wheel angle input during the automated lane changing. A dynamic programming approach to trajectory planning is proposed in this study, which is expected to not only achieve a quick reaction to the changing driving environment, but also optimize the balance between vehicle performance and driving efficiency. First of all, the lane changing trajectory is planned based on the positive and negative trapezoidal lateral acceleration method. In addition, the multi-objective optimization function is built which includes such indexes: lateral acceleration, lateral acceleration rate, yaw rate, lane changing time and lane changing distance. The fuzzy logic controller is designed to distribute the weight coefficient in multi-objective function, which can adapt to different real situations. Subsequently, the optimal steering angle can be derived when the obtained optimum trajectory curve is used as the input of the driver model which based on the preview follower theory. Finally, the vehicle model is built to examine the proposed method using the obtained steering angle as the simulation input. Simulation results demonstrate that the proposed method can guarantee the comfort of the vehicle and the position tracking simultaneously. Additionally, the novel method can make a good balance between the safety and comfort of the passengers.