Research On Lateral Control Of Intelligent Vehicle Based On Simulink Simulation

In recent years,China’s economy has made rapid progress,people’s living standards have been rising,the proportion of disposable income has increased,and cars are rapidly popularized in today’s society and enter people’s daily life.The automobile has promoted the development of social economy and provided a convenient time for people’s daily life,but it has also caused a series of serious problems that threaten people’s lives,such as environmental pollution and traffic accidents.When people explore how to solve these problems,intelligent driving appears in people’s sight.As one of the most critical technology of intelligent driving,the focus of this paper is use lateral control technique to optimize and improve the controller to achieve the purpose of lateral control of the vehicle.The specific research contents are as follows:First of all,the development history of intelligent vehicles at home and abroad and the related research on controllers are analyzed by consulting a large number of documents.Aiming at the problems in the research of lateral control of this paper is established based on model predictive control(MPC),which controls the lateral movement of vehicles and realizes the tracking of vehicle to target trajectory.Then,this paper makes a more in-depth study of the vehicle tire and the vehicle dynamics model,using the magic formula this empirical formula to carry on the nonlinear modeling of the tire and establish the linear working area of the tire;in order to reduce the workload and avoid errors,the tire model should be simplified in linear working area.A three-degreeof-freedom vehicle dynamics model is established based on the characteristics of the vehicle.The vehicle path tracking controller is based on the model predictive control theory.The research focuses on the control stability of the controller and the tracking accuracy of the controller under different vehicle conditions at different speeds.The path tracking level of the controller is simulated by Carsim and Simulink respectively at low and medium speed,and the stability is more significant at low and medium speed.Considering that the vehicle is not always running at a low speed in the actual process of driving,this paper finds the most appropriate controller parameters according to the actual changes of vehicle conditions,so as to ensure that the controller always has a good tracking accuracy and control effect on the vehicle.According to the characteristics of intelligent vehicle with networking function,the stability of the system is analyzed.The model predictive control was used to optimize the lane center keeping auxiliary system iteratively,and the adaptive strategy of vehicle control based on road condition parameter controller was proposed.The most appropriate controller parameters were matched according to different road conditions and vehicle conditions,and the control stability and tracking accuracy of the controller parameters were tested and verified on the co-simulation platform.