Study On Optimal Control Strategy Based On Car-following Behavior Of Autonomous Vehicle

With the development of the national economy and the development of science and technology,people’s demand for driving vehicles is no longer satisfied with the convenience of travel.Intelligent automatic driving vehicles have gradually become new demands for vehicles.In the current study of automatic driving,the driverless vehicle is not put into the real traffic flow to explore,can not improve the safety of the self driving vehicle,and reduce road congestion.Therefore,further research on vehicle following model and control method is of great theoretical significance and practical value.Based on the optimal velocity model,the paper combines the automatic control principle to optimize the vehicle following control.Firstly,in the aspect of car-following model,this paper introduces the optimal speed model under the condition of automatic driving.On the basis of the existing proportional differential and speed feedback control strategies,the feedforward control strategy is introduced into the control of traffic flow of unmanned vehicles.The stability condition of traffic flow is obtained by using Routh criterion and small gain theorem.Through the computer numerical simulation,it is proved that the speed feedback controller,the proportional differential controller and the feedforward controller can effectively improve the stability of the traffic flow system.If the three controllers are combined to form a hybrid compensation controller,the driverless vehicle can not only obtain good stability in the traffic flow,but also quickly restore stability in the face of disturbance.Secondly,the state analysis method and state feedback strategy of modern control theory are applied to the control of automatic driving vehicle traffic flow system,and the interaction between internal variables of car following control system is analyzed.Based on the analysis of the internal variables of the system,the state feedback controller is designed,and the improved transfer function and dynamic equation are obtained.Through the simulation analysis,it is found that the state feedback control strategy has a good control effect on the traffic flow system,which can effectively improve the stability of the traffic flow system,and make the autonomous vehicle obtain more stable car following effect.Then,a more advanced internal model control method is introduced,and a PID controller based on internal model control method is designed.Through MATLAB simulation experiment,it is found that the introduction of internal model controller can effectively improve the stability of traffic flow.On this basis,the concept of maximum sensitivity is introduced,and the internal model PID controller is adjusted based on the maximum sensitivity.The internal model PID controller considering the robustness and stability of the system is obtained,which improves the anti-interference ability of the automatic driving vehicle in the process of car following.Finally,the paper summarizes the innovation points,and lists the shortcomings of the paper and the related work which is still necessary to continue to work and improve in the future.To sum up,this paper combines the autonomous vehicle with car following theory,and uses the control method in the control theory to design the controller,which improves the stability of the car following system and the car following effect of the automatic driving vehicle,and provides a new method for improving the stability and safety of the automatic driving vehicle.