With the rapid development of science and technology, intelligent electric vehicle (IEV) has gradually become the research focus to the scholars. The planning of the trajectory and the accurate path tracking ability are the two key technologies to realize the intelligent driving objective. This paper is conducted in this field that related research about intelligent drive to study the optimal steering wheel angle input.This paper proposes a method that dynamically plans the trajectory, not only to achieve quick reaction to the changing driving environment, but also to optimize the balance between vehicle performance and driving efficiency. First of all, the lane changing trajectory was planned based on the positive and negative trapezoidal lateral acceleration method, synchronously, the multi-objective optimization function was built which comprehensive such indexes: lateral acceleration/ lateral acceleration rate/ yaw rate/lane changing time and lane changing distance. In order to adapt to different trajectory planning optimization researches, the fuzzy logic controller which can adapt to different traffic roads timely was designed. The role of this controller is to adjust the weight coefficient of multi-objective function to realize the tracking control of driver intention real time. Let the optimized trajectory curve what we got from the new idea as the input and with the aid of the driver model that based on preview follower theory the optimal steering angle can be derived, which adapt to follow the actual traffic information real-time. Finally, the vehicle model was built to examine the proposed method, take the steering wheel angle which solved above as the simulation input. Simulation results demonstrate that the proposed method can guarantee both the comfortable of the vehicle and the position tracking synchronization. Simultaneously, the new idea can make a good balance between the safety and comfort to the passengers.