A Longitudinal-lateral Cooperative Control Method For Human-Vehicle-Road Closed Loop System Under Extreme Conditions

With the development of social economy,vehicles are becoming more and more popular as people's common means of travel.At the same time,the number of drivers is growing rapidly.However,due to the lack of experience,some drivers can not timely and effectively control the vehicles under the extreme conditions,resulting in serious traffic accidents.Thanks to the rapid development of vehicle control technology,more and more vehicles are equipped with intelligent control system.On the one hand,it reduces the driver's driving burden,on the other hand,it improves the comprehensive performance of the vehicle.In this paper,the Human-Vehicle-Road closed-loop system is taken as the research object,which focuses on the path tracking and stability performance of the Human-VehicleRoad closed-loop system under the extreme conditions.In the MATLAB/Simulink software,the model of Human-Vehicle-Road closed-loop system is built,and the accuracy of the model is verified by simulation and comparison with the Carsim software.Based on the principle of model predictive control,the path tracking controller is established,which assists the driver by adjusting the driving weight coefficient online,and improves the path tracking accuracy of the Human-Vehicle-Road closed-loop system;The improved Grey Wolf Optimizer is used to establish the vehicle longitudinal and horizontal cooperative controller,which improves the vehicle stability under the extreme conditions by the cooperative control of vehicle longitudinal speed and front wheel angle;Considering the closed-loop extreme condition including the driver,the vehicle can track the path at high speed in a safe and stable state by combining the path tracking controller and longitudinal and horizontal cooperative controller.The main research contents include the following aspects:(1)The Human-Vehicle-Road closed-loop system model is studied.On the basis of the preview follow driver model,a driver model based on the variable preview time of speed is proposed.The 4-DOF vehicle dynamics model based on magic formula tire model is built to form The Human-VehicleRoad closed-loop system model under the single line transfer path,and the simulation is compared with the Car Sim software.(2)The path tracking control method of the Human-Vehicle-Road closed-loop system is studied.Aiming at the problems of low precision and poor robustness of driver model tracking path,a path tracking controller based on model predictive control is established.The path tracking controller's driving weight coefficient is distributed online by fuzzy control,and the path tracking performance of the Human-Vehicle-Road closed-loop system is improved by the control method of Human-Vehicle cooperation.(3)The longitudinal and horizontal cooperative control method of vehicles under the open-loop extreme condition is studied.In view of the problem that the vehicle is easy to lose stability under the extreme conditions,the Lateral-load Transfer Rate and the yaw rate are selected as the stability evaluation indexes,and the longitudinal and horizontal cooperative controller based on the improved Gray Wolf Optimizer is designed.The simulation is carried out under the Fish-Hook and Double-LaneChange conditions with the vehicle longitudinal speed and the front wheel angle as the control quantity,which effectively improves the vehicle stability under the extreme conditions.(4)The longitudinal and horizontal cooperative control system of the Human-Vehicle-Road closed-loop system under the closed-loop extreme conditions is studied.In view of the problem of poor vehicle stability when the driver model is tracking the path at high speed,a vehicle longitudinal and horizontal cooperative control strategy based on the Human-Vehicle-Road closed-loop system is developed.When the Human-Vehicle-Road closed-loop system is running at the closed-loop extreme conditions,the driving control right of the vehicle is transferred to the vehicle controller,which combines the path tracking controller and the longitudinal and horizontal cooperative controller,and the system can track the desired path with high stability.