Research On Obstacle Avoidance Control Methods For Autonomous Electric Vehicle

With the increasing requirement of energy-conservation, safety and intelligence on vehicles, autonomous electric vehicle is attracting more and more attention. Obstacle avoidance method, motion planning and control system are studied for autonomous electric vehicle under different driving conditions. The main research work includes the following four aspects:(1) A set of comprehensive obstacle avoidance strategy is designed and various methods are flexibly choosen to avoid different obstacles. Brake decelerations are determinated based on the analysis of safe brake distance for parking and following mode. The path planning of lane-change mode is researched finally and an efficient method for generating obstacle-avoidance trajectories is proposed.(2) Kinematic model and three DOFs vehicle dynamic model are established for the four-wheel-independently-driven electric vehicle. The co-simulation between Simulink model and CarSim model is conducted and shows the similar characteristics of kinematics and dynamics.(3) A speed-tracking control system is designed, including a fuzzy PID controller calculating the expected torque, a module for torque identification and switch logic and a toqure distribution module. The validation by CarSim shows that, speed-tracking controller can accurately track different speeds; the phenomenon of frequent switching is avoided; driving and braking torques can be flexibly distributed.(4) A lane-change trajectory-tracking control system is designed on the basis of model predictive control. The prediction model, constraints and optimal objective function are defined respectively. According to the co-simulation resluts of Simulink and CarSim, the trajectory-tracking control system can accurately track the lane-change trajectory and the change of front wheel angle is relatively stable. Finally, the effect of different design parameters on tracking accuracy and stability of the controller is analyzed.