Cooperative Control And Optimization Of Shared Intelligent Driving On Ice Snow Covered Pavement

Accurate control of vehicles is a necessary prerequisite for realizing high-quality trajectory tracking of intelligent vehicles of different levels.In northern country,especially in the northeast,frequent snow in the long winter has brought about a lot of traffic and safety problems.The uneven distribution of ice snow covered pavement causes different adhesion coefficients between tires and road surface,which increases the difficulty of vehicle control;ice snow covered pavement will also affect the behaviors of drivers,so,it is significant to study vehicle stability control on ice snow covered pavement.In this paper,the dynamic characteristics of the tire are introduced into the vehicle model to characterize the effect of ice snow covered pavement on the vehicle by influencing the state of the tire.Optimized fuzzy PID control and model predictive control are used to improve vehicle lateral stability;Calculate the objective consistency of controller and driver,an efficient weight allocation method for human-machine control is constructed.The main research work of this paper is as follows:1.Design a vehicle dynamics model considering tire characteristics on ice snow covered pavement.The uneven distribution of adhesion coefficient on ice snow covered pavement leads to the asymmetry of tire force,so it is necessary to analyze the force and movement characteristics of each tire.The longitudinal force and lateral force of the tire are calculated based on the slip rate of the tire and the pavement adhesion coefficient.The vehicle dynamics characteristics with the asymmetric tire force on the ice snow covered pavement are built,which lays the foundation for the subsequent control algorithm design.2.Aiming at the lateral stability control of vehicles,the model prediction controller and the optimized fuzzy PID controller are designed respectively.A BP neural network with weighted pavement adhesion coefficient and vehicle longitudinal speed as input and PD scaling coefficient as output is constructed to optimize the fuzzy PID.Based on vehicle model characterizing the ice snow covered pavement,the model predictive controller constructs the constraint conditions and objective functions to realize the lateral stability control of the vehicle.3.Aiming at the target conflict in the human-machine cooperative control,the control weight distributor is designed.Based on the increment of the driver and the controller’s output,objective consistency and human-machine control weight are calculated to realize indirect shared control.4.Realize simulation experiment based on CarSim/Simulink,and the real vehicle experiment based on Linux and C++.ROS is used to realize the communication between nodes,and the vehicle position and status information is obtained through the sensor.The control algorithm calculate the target steering angle according to the trajectory error,and the effectiveness of the control algorithm in the real vehicle situation is verified.