Research On Path Tracking And Ground Control Of Intelligent Vehicles

While bringing convenience to people,automobiles also cause many social problems.The most serious problem is the traffic safety problem,and the main cause of traffic accidents is the improper operation of the driver.Therefore,researches on intelligent vehicles have been carried out at home and abroad in an attempt to free drivers and solve traffic safety problems.Among them,path tracking and ground control have always been one of the key technologies for smart vehicles.To this end,this article first introduced the research background and research significance of intelligent vehicle,and the research status of intelligent vehicle path tracking at home and abroad is introduced.At present in the high speed,rain and snow,low adhesion road and other complex driving scenarios,path tracking accuracy,real-time and robustness still can not meet the actual needs,and urgent research on Intelligent Vehicle Routing in complex driving scene tracking technology is still very necessary.On this basis,this paper introduces the research content and chapter arrangement.Then,the basic principles of model predictive control(model-based prediction,rolling optimization,feedforward-feedback control structure)are introduced.Aiming at high speed,rain and snow,low adhesion road under complex driving scene,the path tracking model predictive controller requires a vehicle dynamics model as a predictive model to predict the future dynamics of the vehicle and optimize the solution.Therefore,the dynamic model of the vehicle is studied,a three-degree-of-freedom vehicle dynamic model and a magic formula tire model are established,and the characteristics of the tire model are analyzed.Based on the above theoretical research,a path tracking controller based on nonlinear model predictive control is established.In order to improve the real-time performance of the system,the prediction model is linearized and discretized.A path tracking controller based on linear time-varying model predictive control is proposed.In order to ensure the accuracy of the path tracking and the stability,ride comfort and comfort of the vehicle,an objective function is established to punish the tracking deviation and the control increment respectively.In addition,control increments,control variables,and output constraints are proposed.In order to ensure the stability of the vehicle and satisfy the construction of the vehicle in the linear region of the tire,a tire lateral deflection soft constraint is proposed.Finally,the optimization problem is transformed into a standard quadratic programming problem,and the first element of the optimal control sequence is applied to the system as an actual control increment.In addition,the underlying control of the intelligent vehicle is studied.First of all,the overall scheme of the bottom control of intelligent vehicles was proposed.Then,the underlying hardware of the intelligent vehicle was designed.The steering system of the vehicle was modified and a power supply system was designed.The basic principle of PID control is introduced.The PID-based lateral controller was proposed on the basis of the online-controlled steering system.Finally,a joint simulation platform for Carsim and Simulink was built.Simulations of path-following controllers based on linear time-varying model predictive control(without considering lateral tire angle constraints)and the underlying controllers under different attachment conditions and different travel speeds,verifying that linear time-varying model-based predictive control The path-tracking controller(without considering the tire side-deflection angle constraint)and the underlying controllers are robust to speed,but under low-adherent road surfaces,the tracking deviation is large and the vehicle exhibits a destabilizing linearity.Therefore,the tire side flank angle soft constraints are increased,and the path tracking controller based on the linear time-varying model predictive control(taking into account the tire side slip angle constraint)and the bottom controller are simulated under low adhering road conditions and different driving speeds.It shows that the path tracking controller considering the tire side slip angle and the underlying controllers are robust to the adhesion coefficient.