Research On Intelligent Vehicle Formation And Obstacle Avoidance Based On Trajectory Tracking

Multi-intelligent vehicle formations have a wide range of application prospects in the fields of intelligent transportation systems,military,road traffic and transportation,and have received extensive attention and research from many scholars at home and abroad in recent years.In recent years by many scholars at home and abroad extensive attention and research.Considering the problem of intelligent vehicle formation keeping and obstacle avoidance control in the complex actual driving environment,this paper studies the intelligent vehicle formation control method based on trajectory tracking,the double closed-loop control strategy in the case of vehicle longitudinal skidding,the adaptive sliding film control in the case of vehicle steering actuator failure and the vehicle formation obstacle avoidance algorithm in the presence of obstacles.Simulation experiments are designed to verify the effectiveness of the proposed algorithms.The main work is as follows.(1)The vehicle kinematic model is established according to the kinematic constraints and geometric relationships of intelligent vehicles,and the vehicle kinematic model is refined by considering the vehicle longitudinal slip and steering actuator failure.The system state error equation of the preset formation is established by combining the virtual structure formation strategy and coordinate transformation.The formation system error state equation is optimized by selecting the same reference points of the virtual reference vehicle and the following vehicle.(2)For the intelligent vehicle formation position control problem,firstly,a feedback linearization controller satisfying Lyapunov stability is designed.Secondly,considering the existence of longitudinal slippage of intelligent vehicles,on the basis of the designed feedback linearization control,a double closed-loop formation controller with speed compensation is designed using the actual vehicle speed obtained by sensors.And RBF neural network is used to rectify the parameters of the inner-loop speed compensation controller to improve the formation accuracy under the existence of longitudinal slippage of intelligent vehicles.(3)For the problem of intelligent vehicle steering actuator failure,firstly,considering the existence of modeling error in the vehicle equation of motion,the integral sliding mode controller is designed.Secondly,considering the existence of failure in the intelligent vehicle steering actuator,the intelligent vehicle angular velocity adaptive sliding mode controller satisfying Lyapunov stability is designed.And MATLAB is used for simulation,and the effectiveness of the designed control rate and adaptive rate is verified by the set simulation experiment.(4)For the problem of obstacle avoidance in the process of intelligent vehicle formation driving,firstly,the traditional artificial potential field method is improved.And an obstacle avoidance path is planned for the formation reference vehicles by the improved artificial potential field method.Secondly,the artificial potential field algorithm and the virtual structure formation strategy are combined.And the trajectory planned by each virtual reference vehicle can achieve obstacle avoidance as well as formation maintenance by constructing gravitational potential field,obstacle repulsion potential field,and workshop anti-collision repulsion potential field.