Abstract: To solve the problem of trajectory tracking accuracy and control stability of driverless vehicles, a method that considers feedforward control and dynamically adjusts speed PID controller parameters is proposed. Seven polynomial is used for lane change trajectory planning, the double PID controller of longitudinal position and speed is improved, the longitudinal displacement error is adjusted dynamically, and the PID parameters are adjusted in real time. Meanwhile, the lateral displacement error and the pendulum velocity error are solved, making the tracking error converge, and finally the control amount is converted into the desired front wheel angle through the motor model, thus solving the problem of large lateral tracking error caused by the model mismatch. By simulation verification, when the vehicle is running in the urban road scene at 60 km/h, the transverse displacement error is controlled within 0.015 m, the longitudinal displacement error is controlled at mm level, and the error range is controlled at [0.002,0.006] m. The speed of the body is stable and the speed error is not more than 0.83 rad/s. On this basis, the real vehicle experiment is further completed. The results of both simulation and real vehicle experiment show that the designed controller can meet the requirements of high precision in trajectory tracking and ensure the smooth driving of driverless vehicles in the lane change condition.

Key words: unmanned driving, parameter-adaptive, Proportional Integral Derivative(PID), fuzzy control, Linear Quadratic Regulator(LQR), trajectory tracking