Study On Model Predictive Control Method For Trajectory Tracking Control Of Autonomous Vehicles

The increasing complexity of traffic environment and the limitation of traditional driving mode have promoted the improvement of vehicle automation,and the corresponding auto-driving technology has also been developed rapidly.The autonomous driving technology of vehicles can not only liberate the human drivers,but also greatly improve the safety of driving and the orderliness of the traffic.Trajectory tracking control is not only one of the key points in the research of vehicle automatic driving technology,but also the key technology to realize the intelligent transportation system.So,the study of vehicle trajectory tracking control is of great significance in the realization of autonomous driving of vehicles.In this paper,Model Predictive Control method is used to study the trajectory tracking control of autonomous vehicles.Firstly,the necessity of using linear time-varying Model Predictive Control method in vehicle trajectory tracking control is explained.And aiming at the characteristics of vehicle nonlinearity and multi-constraints,considering the lateral,longitudinal and yaw motion of vehicle under certain assumptions,a three-degree-of-freedom dynamic model of the vehicle is established and linearized and then discretized.Then,based on the linear time-varying Model Predictive Control and the tire model based on magic formula,the vehicle dynamic model is transformed into the predictive model,and giving various input and output constraints in the process of vehicle movement.The objective function used to optimize the solution of the control quantity is designed and transformed into a Quadratic Programming problem which is easier to solve.The design of trajectory tracking controller based on Model Predictive Control is completed.Finally,the trajectory tracking controller is simulated and analyzed on the simulation platform of Matlab/Simulink/Carsim under different road adhesion coefficients and different vehicle speed conditions.The simulation results verify the effectiveness of the trajectory tracking controller based on Model Predictive Control under different working conditions.