Research On Lane Keeping Control System Based On Man-machine Mutual Driving

In the case that the regulations and technologies related to autonomous vehicle are still immature,the development of advanced driver assistance systems has become a major research direction.As a major part of advanced driver assistance systems,the lane keeping system can effectively improve the active safety of the car.However,most of the current lane keeping systems regard the driver's operation as outside interference after the vehicle deviates from its own lane.If the lane keeping control system is significantly in conflict with the driver,the driver's driving experience will be affected.Therefore,this paper will study the lane keeping control system based on man-machine mutual driving.Firstly,a lane departure decision model is established.Since a single lane departure decision model has its own advantages and disadvantages,it cannot guarantee the accuracy of its algorithm while improving its early warning accuracy.Therefore,this paper adopts the lane departure decision based on the combination of safe driving area and the latest early warning boundary.The model reduces the complexity of the early warning algorithm while improving its early warning accuracy.The dynamic threshold method is adopted to dynamically adjust the warning threshold according to the vehicle driving state and the road surface adhesion coefficient,and the algorithm is verified by the joint simulation of Carsim and Simulink.Secondly,the vehicle lateral control algorithm is established.In the vehicle lateral control algorithm,the cascade MPC-PID control strategy is adopted,and the prediction model is established according to the vehicle lateral dynamics model.Then,the optimization objective function is established and the control quantity constraint is added to the sub-optimization problem,and the optimal problem is transformed into the quadratic programming to get the target front wheel angle.Finally,the tracking of the target front wheel angle is completed by using the PID.In order to verify the accuracy of the algorithm,the algorithm is verified by double shift line condition and serpentine condition.In order to reduce the conflict between the auxiliary control system and the driver,the control right of the vehicle is allocated by using the mutual driving coefficient.In order to make the mutual driving coefficient dynamically adjust according to the running state of the vehicle and the driver's operation,the fuzzy control is used to dynamically adjust the mutual driving coefficient,and the lateral position error and direction error of the vehicle are adjusted to the vehicle state error,its and the driver's steering torque are regarded as input variable of fuzzy control together.The mutual driving coefficient is used as the output variable of fuzzy control,so that the lane keeping control system can reduce the man-machine conflict while ensuring its function.Finally,the electric power steering unit is used as the execution module of the lane keeping control system,and the electric power steering model is modeled,and the model is verified by three typical working conditions.In order to simulate the driver's inattention or fatigue state,the driver model is established to lay the foundation for the simulation analysis of the subsequent vehicle control algorithm.The simulation of the proposed control strategy is verified by the Carsim/Simulink.The results show that the mutual driving coefficient can be dynamically adjusted according to the driver's operation and the change of the running state of the vehicle,which prevents the vehicle from deviating from the lane while preserving the driver's certain operation,and reduces the collision between man and machine.