Optimal Modeling And Energy Consumption Control Of Traffic System Based On Cooperative Information Transmission Delay Under V2X Environment

As the problem of traffic congestion becomes more and more serious,which has a great impact on the efficiency of urban operation,the research on traffic flow theory has also received attention from scholars.In recent years,with the progress of communication technologies such as V2 X,it has brought new inspiration to the research of traffic flow theory,and the intelligent transportation system has also obtained a larger development platform.Therefore,improving the increasingly prominent traffic congestion problem based on the theoretical framework of traffic flow and using communication technology as a technical support has become a hot research topic in the field of traffic flow at present.In recent years,the application of delayed-feedback control method in traffic flow has attracted more and more attention of scholars.In this paper,some corresponding traffic models are established by considering the synergistic transmission effect of various delayed information,and relevant conclusions are drawn through mathematical analysis and simulation experiments.The main contents of this thesis are as follows:Firstly,a lattice hydrodynamic model base on the coordinated transmission effect of density and flux delay is established.The neutral stability curve and coexistence curve are drawn through theoretical analysis,and it is found that the model has a strong stability.The simulation results show that when the lattice model considers the synergistic effect of density and flux delayed information,it can significantly cut down the volatility of the density and flux curves,and also has the characteristics of reducing traffic energy consumption.Secondly,this paper applies the cooperative information transmission delayed effect to the car-following model.Via linear analysis and derivation of its m Kd V equation,the results show that the car-following model by considering the CITD effect of headway and velocity has stronger stability.And in the numerical simulation,it is found that the CITD effect has the advantages of stabilizing the headway,reducing the hysteresis phenomenon of traffic system,and lessening the additional traffic energy consumption.Then,this thesis constructs an extended car-following model based on the effect of evolutionary information continuous memory.Through linear and nonlinear analysis,it is found that the model has a larger stable region.The numerical simulation result reveals that when the EICM effect is considered in the car-following model,it can achieve the purpose of stabilizing the vehicle spacing,cutting down the hysteresis phenomenon,and reducing traffic pollution emissions.Finally,this paper applies the EICM effect to the lattice hydrodynamics model.The results reveal that the lattice model considering the EICM effect can improve the stability of traffic flow and weaken the fluctuation of density and flux curves.In addition,through the fuel consumption simulation experiment,it is found that the EICM effect also has the advantages of decreasing traffic fuel consumption and improving fuel efficiency.In conclusion,the car-following model and the lattice control model considering the synergistic transmission effect of various delayed information can improve the stability of traffic flow and relieve traffic congestion under the V2 X environment.In addition,these effects also have the advantages of reducing transportation energy consumption,pollution emissions,and fuel consumption.This research provides a certain theoretical basis and development ideas for traffic optimization,control,and research and development of intelligent transportation.