Trajectory Tracking Automatic Driving System Based On Model Predictive Control

The self-driving car is a kind of intelligent car that realizes driverless driving through a computer system,and is a comprehensive product of a collection of advanced technologies in various fields.Perception,decision-making,and planning control are the three cores of autonomous vehicles,enabling vehicles to sense and understand the driving environment,make active decisions,plan real-time paths to global or local maps,and accurately control vehicle motion and track desired trajectories.Meet the desired driving requirements.As one of the cores of planning control,rational planning of trajectory and smooth motion control is the key to achieving automatic driving.In this paper,by studying the trajectory tracking control in automatic driving,a trajectory tracking automatic driving system based on model predictive control is designed.In order to realize the tracking of the desired trajectory of the autonomous vehicle,the vehicle state representation model under the road Frenet coordinate system is first established.In order to construct the controller using the vehicle model,the kinematics and dynamics of the vehicle are analyzed,and the physical model of the vehicle is established.The vehicle longitudinal position error,longitudinal velocity error,lateral position error,lateral velocity error,heading angle error,The heading angular velocity error is used as the state of the state space,and the state space model is constructed with the steering angle and acceleration and deceleration as the control amount of the state space.Based on the vehicle state space model,the predictive model of model predictive control is constructed.The model predictive control is applied in the trajectory tracking control.The process model under the control is used to predict the future state of the vehicle,and the predictive model is converted into a quadratic optimization problem.The control quantity constraint is solved by solving the quadratic optimization problem,and the optimal control quantity of the trajectory tracking control is obtained by rolling.Through the ROS robot system and GAZEBO simulation platform,the trajectory tracking autopilot system based on model predictive control is simulated.The simulation shows that the autopilot system runs stably and has better trajectory tracking effect.The model predictive control algorithm is validated.Reliability and effectiveness in autonomous vehicle trajectory tracking.Considering the difference between simulation and reality,in order to further research and verify the system,build a 1/10 proportional physical vehicle and use NVIDIA Jetson TX2 as the running platform to conduct actual test on the trajectory tracking automatic driving system based on model predictive control.It shows the feasibility of hardware selection and hardware system framework,and the reliability and effectiveness of the trajectory tracking autopilot system based on model predictive control in practical applications.