Research On Integrated Trajectory Tracking Control Of Four Wheel Steering Autonomous Vehicle

The autonomous vehicle will encounter extreme conditions in trajectory tracking,such as strong crosswind,high-speed driving,low adhesion road,and small turning radius curve.To maintain good anti crosswind,anti sideslip,anti rollover,and obstacle avoidance performance under extreme conditions,and to minimize the trajectory tracking deviation,an active disturbance rejection control(ADRC)trajectory tracking integrated controller is proposed to decouple the steering,braking,and suspension systems,which is used to improve the trajectory tracking accuracy,safety,and stability performance of autonomous vehicles under extreme conditions.To plan the target trajectory of standard single center curve without the data of electronic map table,the quadrant of curve and the driving direction are introduced,and the polar coordinate equation is used to plan the target trajectory of single center curve.The trajectory of obstacle avoidance target with large curvature and sharp turning is planned by quintic polynomial.Considering the transformation relationship between vehicle coordinate system and earth inertial coordinate system,a conversion method is proposed to convert target trajectory into initial steering angle input of autonomous vehicle.To obtain the tire longitudinal and lateral force in trajectory tracking,the tire longitudinal and lateral force under different tire loads of tire model(215/55 R17)is estimated by slip combination theory,trigonometric function group fitting,and cubic spline interpolation.This method not only reduces the complexity of tire longitudinal and lateral force estimation,but also improves the estimation accuracy.To obtain vehicle state parameters and road adhesion coefficient in trajectory tracking,an extended Kalman filter(EKF)estimator is designed to estimate vehicle state parameters and road adhesion coefficient.The test results of right angle curve show that the EKF estimator can accurately estimate vehicle state parameters and road adhesion coefficient.According to the estimated road adhesion coefficient and tire longitudinal and lateral force limit value,the limit conditions of autonomous vehicle are set.To avoid understeer caused by excessive steering angle frequency or high vehicle speed when tracking the desired yaw rate of four-wheel steering(4WS)autonomous vehicle,a feedforward compensation method for initial input of 4WS autonomous vehicle is proposed based on frequency domain response and error curve of first-order lag system.According to the change of vehicle speed and steering angle frequency,it can linearly compensate the desired steering sensitivity amplification coefficient of 4WS autonomous vehicle,thus reducing the deviation between the actual value and the expected value of yaw rate,and improving the accuracy of tracking the desired yaw rate.The results of high-speed emergency obstacle avoidance simulation test show that the 4WS autonomous vehicle with feedforward compensation method can not only minimize the tracking error of obstacle avoidance trajectory,but also significantly reduce the probability of not being able to avoid obstacles,sideslip,tail flicking,or running out of the runway after obstacle avoidance.To improve the trajectory tracking accuracy,safety,and stability performance of 4WS autonomous vehicle under extreme conditions,combining the three channel ADRC trajectory tracking feedback controller which can decouple the steering and braking system and the four channel ADRC anti roll controller which can compensate the spring force of suspension,a seven channel ADRC trajectory tracking integrated controller which can decouple the steering,braking,and suspension systems is completed.It can compensate the deviation between the actual value and the desired value of the longitudinal and lateral displacement through the front wheel steering angle,the deviation between the actual value and the desired value of the yaw angle can be compensated by the yaw moment,and the deviation between the actual value and the desired value of the vertical displacement at the four ends of the vehicle body through the suspension spring force.The anti sideslip performance and trajectory tracking accuracy of 4WS autonomous vehicle on wet low adhesion curve are effectively improved by the integrated controller.The anti rollover performance and trajectory tracking accuracy of high center of gravity(CG)sport utility vehicle(SUV)on small turning radius curve are effectively improved by the integrated controller without reducing the trajectory tracking performance and vehicle speed.The high-speed simulation test on real continuous variable curvature curve shows that the integrated controller can effectively improve the trajectory tracking accuracy,safety,and stability performance of 4WS autonomous vehicle in real variable curvature curve.The real vehicle curve tracking tests show that the autonomous vehicle with the integrated controller(only the first and second channels open)has good curve trajectory tracking performance under small turning radius curve low speed driving conditions.