Research On Longitudinal Following Control Of Intelligent Fleet Considering Vehicle-to-vehicle Communication Delay

With the continuous increase of car ownership,problems such as traffic congestion,environmental pollution and traffic accidents have become increasingly prominent.Therefore,finding feasible and effective solutions has become a top priority in transportation work.In recent years,vehicle platoon control has become a research hotspot in the field of intelligent transportation,and is expected to solve the above-mentioned traffic problems.However,in practical applications,the vehicle queuing system is a complex nonlinear multi-constraint system,and because the vehicles in the queue transmit information through the wireless network,there is often a delay in the communication link,and it is difficult for the controller to accurately obtain the information of the preceding vehicle.The state of motion affects the stability of the vehicle queue and the control effect.In view of the above problems,this paper proposes a longitudinal following control method for intelligent fleets considering the communication delay based on the Model Predictive Control(MPC)algorithm and the Kalman Filter(KF)principle.The stability and control effect of vehicle platooning.The specific research contents are as follows:(1)Design the lower-level control method based on the inverse longitudinal dynamics model.On the basis of vehicle longitudinal dynamics analysis,the lower-level control method is designed with the Carsim vehicle model as the controlled object.The lower layer control includes three parts: drive/brake switching control strategy,lower layer drive control,and lower layer brake control.After the design of the lower layer control method is completed,the effectiveness of the lower layer control method is verified under typical driving conditions.(2)Design the upper layer control algorithm based on KF and MPC.In the upper control design,based on the feedback linearization theory,vehicle queue control system is linearized.On this basis,the control law is derived according to the principle of the MPC algorithm,and the control objectives and constraints of the system are determined.Considering the influence of communication delay on vehicle platoon control,an algorithm combining KF and MPC algorithms—KF-MPC algorithm is proposed to ensure the control performance of vehicle platoon longitudinal following system under the influence of communication delay.(3)Build a Carsim/Simulink co-simulation experiment platform to study the control performance of the KF-MPC algorithm under the influence of fixed communication delay.Build the vehicle dynamics model in Carsim and build the control model in Simulink.Under three typical simulation scenarios of constant speed,continuous acceleration/deceleration,emergency braking and fixed delay conditions,the effectiveness of the proposed KF-MPC control method is verified,and the control performance of the PID and MPC algorithms is compared.Compared.The results show that compared with the PID and MPC algorithms,the KF-MPC algorithm can effectively suppress the fluctuation of vehicle speed and the following lag phenomenon in the intelligent fleet caused by the communication delay,and ensure the effect of vehicle platoon control.(4)Based on the KF-MPC control method,the longitudinal following control of vehicle platoons under the condition of random communication delay is studied.In view of the random characteristics of network delay,this paper uses the Rand function to generate random numbers in the range of 10～100ms,and uses the random number as the input of the delay module,then under the three scenarios of constant speed,continuous acceleration/deceleration,and emergency braking,the control performance of the KF-MPC algorithm is verified and compared with the control effects of the PID and MPC algorithms.The simulation results show that under the influence of random communication delay,compared with PID and MPC algorithms,KF-MPC has smaller vehicle speed fluctuation and vehicle spacing error in the control process,which can ensure the control of the intelligent fleet longitudinal following control system performance.