Research On Active Path Tracking And Collision Avoidance For Autonomous Electric Vehicle

In recent years,with the growing number of the car ownership,environmental pollution,energy shortage and other problems are becoming more and more serious.People have put forward higher requirements for environmental protection,energy consumption and occupant safety.With the rapid development of sensor technology,computer science and control technology,the vehicle technology is progressively developing from level 2(partial automation)to level 3(conditional automation),and will eventually achieve full automation.The autonomous vehicle could totally replace the drivers' operation,which could minimize the traffic accidents caused by the drivers' errors,reduce the driving load,improve traffic efficiency and reduce the vehicle emission effectively.As the fundamental function of the autonomous vehicle,the vehicle chassis control for path tracking and collision avoidance can ensure the vehicle track the desired trajectory stably and accurately,which is of great significance to ensure the stability and safety of autonomous vehicle.Aiming at the autonomous path tracking and collision avoidance control for autonomous electric vehicle,the main contribution of this dissertation is as follows:According to the nonlinear and coupling characteristics of vehicle dynamics,the 15-DOF nonlinear vehicle dynamic model is established to accurately describe the vehicle dynamics based on the Newton's second law and D'Alembert's principle,which include vehicle body motion model,wheel dynamic model and tire model.Then the coupling characteristics are analyzed.Considering the requirement of path tracking controller,the simplified 8-DOF plane motion dynamic is established,which improves the computation efficiency on the premise of guarantee the model accuracy and lays the foundation of the research on the autonomous path tracking and collision avoidance.As for the vehicle longitudinal collision avoidance problem,the vehicle risk assessment model is established By using the artificial potential field theory.Balancing the driver's expectation,collision risk and ride comfort,the optimization problem is formulated based on the model predictive control to calculate the desired longitudinal force.Based on the vehicle longitudinal force demand,the torque vectoring algorithm is proposed to achieve the optimal driving/braking torque distribution,which effectively realizes the safe and smooth following and emergency braking fuction under different road conditions,and improves vehicle longitudinal stability.Due to the complex environment and variable road parameters,a hierarchical based chassis path tracking control algorithm is proposed in order to improve the vehicle path tracking accuracy and stability.Firstly,the nonlinear model predictive control theory is adopted to establish the optimization problem according to the vehicle lateral position error and speed limit.Then,the optimal torque vectoring algorithm is adopted in the lower level controller to balance the vehicle stability and motility demand.Such control method effectively ensures vehicle has satisfactory tracking performance and remains stable under different road conditions.During the vehicle path tracking process,the model uncertainty,external disturbance and actuator fault may impact the vehicle tracking performance.To solve such problem,a robust path tracking control considering actuator fault is proposed.In view of the change of vehicle speed and the influence of the potential failure risk of the actuator on the system,a linear parameter varying model with parameter uncertainty is established,and the time-varying parameters in the state equation are processed by the polyhedron model.Based on the linear matrix inequality,the output feedback robust fault tolerance controller is designed considering the system stability,input constraints and pole location.Such control method could maintain system stability and tracking accuracy when vehicle speed changes and actuator failure occurs.When obstacles occur during the path tracking process,vehicle can't continue track the desired trajectory.To solve such problem,the hierarchical based lateral collision avoidance control strategy is proposed.The local collision free path planner is established based on the rigid body motion model.The local collision avoidance path optimization model is designed based on the model prediction theory.According to the relative motion state of the obstacles,the linear partial collision avoidance constraint is designed to regulate the local path and the vehicle speed in real time,which ensures vehicle collision avoidance.