Research On Intelligent Vehicle Motion Planning And Control Method In Complex Environment

Intelligent vehicles are a comprehensive product of a new round of technological revolution,and have important historical node significance for current traffic safety,energy conservation and environmental protection.This paper takes intelligent vehicles as the research object,and studies its key technology motion planning and motion control methods.The significance of the research is to continuously improve the relevant important technologies of smart vehicles,and gradually expand the application scenarios of smart vehicles,so that smart vehicles can better meet People’s new needs in the new era.The specific research content of this paper is as follows:(1)Carry out vehicle system modeling from the perspective of intelligent vehicle motion planning and motion control.First,a simplified vehicle kinematics model was established for the kinematic constraints of smart vehicles in motion planning and low-speed driving conditions during motion control;then a dynamic model combined with the tire model was established,and the real-time nature of the tracking control algorithm was considered.The problem is that the vehicle’s lateral dynamics model is assumed to have a small slip angle,and the vehicle lateral dynamics model based on the small slip angle assumption is completed.(2)Based on the established vehicle kinematics model,an intelligent vehicle motion planning method based on the improved APF algorithm is established.First,add an adjustment factor to the original repulsion function to make the algorithm effectively avoid the extreme value problem;then,add dynamic obstacle constraints to construct the repulsion potential field,so that the generated trajectory vehicle can safely follow.Then,using the geometric dimensions of the vehicle and the dynamic and static obstacles,the separation axis theorem is used to conduct collision detection to ensure the safe driving of the vehicle.Finally,the improved APF algorithm is simulated and verified based on Matlab,and the vehicle verification of the improved APF algorithm is carried out.The simulation results show that the trajectory planned by the improved APF algorithm proposed in this paper can effectively avoid dynamic obstacles,and finally generate a trajectory that can meet the safety of the vehicle.The verification results of the smart model vehicle show that the smoothness of the planned trajectory and the length of the planned trajectory of the improved APF algorithm are better than the commonly used RRT* planning algorithm for smart vehicles.(3)Based on the sliding mode variable structure control(SMC)algorithm,the intelligent vehicle motion tracking controller is designed.First,the basic principles of sliding mode variable structure control are briefly introduced;then,based on the vehicle kinematics model and sliding mode variable structure control algorithm established above,an SMC motion tracking controller based on vehicle kinematics is designed,and the positions are respectively performed.The design of the control law and the attitude control law,and the simulation verification analysis based on Matlab,the results show that the designed sliding mode controller can quickly track the desired trajectory and achieve stable motion control;then,the vehicle under the assumption of small tire side slip angle Lateral dynamics model and sliding mode variable structure control algorithm,SMC motion tracking controller based on vehicle dynamics is designed under the background of front wheel active steering,and observer is designed to estimate the unmodeled dynamic state quantity of the system,Combined with the design of SMC motion controller based on the combined reaching law and non-singular terminal sliding mode to design the nonlinear error feedback control law,and based on the Lyapunov stability theory for stability analysis,improve the system’s convergence speed and control accuracy.(4)A CarSim/Simulink co-simulation platform was built to verify and analyze the stability of the controller designed based on the lateral dynamics model of the vehicle.First,the intelligent vehicle simulation model was established based on CarSim;then,using the lateral dynamics motion controller built in Simulink in Chapter4,the intelligent vehicle motion control CarSim/Simulink co-simulation platform was built to verify different vehicle speeds and the performance of the designed controller under different road adhesion coefficients.The simulation results show that the controller designed in this paper has high motion tracking accuracy,strong robustness and does not rely on accurate mathematical models,and has a good engineering application prospect.