Collaborative Modeling And Pollution Emission Control Based On Information Feedback Transmission Under V2X Environment

In recent years,with the development of the economy,the number of vehicles on the road has increased rapidly,and the phenomenon of traffic congestion can be seen everywhere.Traffic congestion will not only cause waste of energy,but also pollution to the environment.While people worry about this,it also promotes the development of traffic flow theory,Experts and scholars at domestic and abroad have proposed a series of traffic flow models for the internal formation and propagation mechanism of traffic congestion.Among them,the coupled mapping（CM）car following model not only has a simple algorithm form,but also can describe complex traffic phenomena,which can provide theoretical basis for future intelligent transportation.Therefore,this paper draws on the CM model as the theoretical basis for related research.Meanwhile,with the advancement of technology,the Internet of Vehicles technology has also emerged as the times require.Vehicle to everything（V2X）is the key technology of future intelligent transportation system.It enables real-time communication between vehicles and vehicles,vehicles and base stations,base stations and base stations,so as to obtain real-time road conditions,pedestrian information and a series of traffic information in time.Therefore,collaborative modeling based on information feedback transmission under the V2X environment has important practical significance.Based on the CM car-following model,this paper comprehensively considers realistic factors such as the estimated optimal velocity,the synergy of driver sensitivity and time-varying safety distance,establishes the corresponding dynamic model,and uses the method of feedback control theory for stability analysis.The stability conditions are obtained,and the validity of the model on congestion control and pollution emission control is verified by numerical simulation.The main contents of the thesis are as follows:I.OEVD-CM car-following model is proposed by considering the influence of the difference of the estimated optimal speed based on the Konishi’s CM car-following model under V2X environment.The stability of the new model is analyzed by applying the control theory,and the conditions are obtained for the stability of the traffic system.And the two scenes of vehicle stopping once and four times have been simulated.The simulation results show that the control term considered with optimal estimation of speed difference can effectively improve the stability of vehicle running and reduce CO₂ emissions in the CM car-following model.II.AOVD-CM car-following model is constructed by considering the feedback control influence of the deviation between the anticipation optimal speed and the actual running speed on the traffic flow under the V2X environment.The gain range of feedback control is deduced from the stability condition of the traffic system with the consideration of the anticipation optimal velocity deviation effect by applying the modern control theory method.Numerical simulation has been carried out at the cases of the leading vehicle stopping one time and four times.The simulation results demonstrate that the anticipation optimal velocity deviation effect in CM car-following model can curb congestion and effectively reduce pollutant emission pollution such as CO₂,NOx,PM10 and stabilize VOC emissions.III.Next,we provide SOVD-CM car-following model integrating the self-anticipated optimal velocity difference effect under the V2X environment.Applying the feedback control theory,we obtain the conditions for the traffic flow to remain stable when the leading vehicle’s velocity changes and get the value range of the feedback gain.The numerical simulations are respectively executed for two cases including leading car occurring one stop and four stops under the open boundary condition.Numerical simulation results verify the correctness of the theoretical analysis.It is importantly found that the SOVD effect can effectively alleviate traffic congestion and reduce fuel consumption,CO,HC and NOx emissions.Meanwhile,we also respectively investigate the influence of the leading vehicle’s stopping number and stopping time on the fuel consumption rate and pollutant emission rate for the Konishi’s CM car-following model and the SOVD-CM car-following model,respectively.IV.At last,in order to get closer to the real traffic environment,we comprehensively consider the synergy of driver sensitivity and time-varying safety distance under the V2X environment,and proposes SSSD-CM car-following model.Using cybernetic methods to obtain the conditions for the stability of the traffic system,besides,we consider that the leading vehicle stops and starts slowly.The numerical simulation of the scenes of the leading vehicle stops once and continuously is carried out.The results show that:the new model can effectively improve the traffic environment,and the energy consumption control has also been greatly improved.