Micro-driving Behavior Modeling And Stability Analysis In The Internet Of Vehicles Envrionment

As the number of motor vehicles continues to increase,the problem of traffic congestion is becoming more and more serious,causing a lot of inconvenience to people's daily travel,and further causing a series of negative problems such as traffic safety,energy consumption and environmental pollution.At present,the speed of infrastructure construction lags far behind the growth of people's travel demand.Therefore,how to scientifically deal with the world problem of imbalance between transportation supply and demand,and to improve people's travel quality and urban ecology have become important issues to be solved urgently at this stage.The emergence of Internet of Vehicles technology has brought new opportunities for solving traffic congestion problems.Under this technology,vehicle status information such as velocity,acceleration,and headway between vehicles can be shared in real time,then collaborative driving between vehicles can be achieved according to the range of information transmission.In this paper,based on the Internet of Vehicles environment,starting from the characteristics of vehicle operation in the new traffic environment and the interaction mechanism between vehicles,microscopic road traffic flow model are constructed.Through theoretical analysis and numerical simulation,various traffic flow measurement phenomena in the vehicle network environment are studied,and further explore the impact of information reliability on traffic flow dynamics.The specific research work is as follows:(1)Based on the Newell model,a car-following model considering the Headway Variation Tendency(HVT)is proposed.The vehicles in the actual traffic system are moving at the same time,subject to the limitations of detection technology and information technology.Existing traffic modeling does not explain this microscopic traffic phenomenon very well.The driver can predict the movement trend of the vehicle at the next moment in the connected vehicle environment.Based on this,this paper builds a microscopic road traffic flow model that can describe the actual car following behavior.Through linear stability analysis theory,the model is analyzed analytically,and the influence of different prediction time on the stability of traffic flow was given.Based on the linear stability analysis,the perturbation method was used to further analyze the model nonlinearly to accurately describe the evolution characteristics of traffic near the critical point.Finally,the validity of the model is verified by numerical simulation.(2)Based on the downstream traffic conditions,the paper establishes a new car-following model with Multiple Headway Variation Tendency(MHVT).Downstream traffic flow conditions have a significant impact on the current vehicle operating state.If the current vehicle obtains the status information of the downstream vehicle,frequent acceleration or deceleration can be avoided,and the occurrence of disturbances can be reduced.Benefiting from the connected vehicle technology,this paper integrates the status information of the downstream vehicles into the model in the research content(1)to build a micro-following model with multiple expectation effects.With the help of the stability analysis method,the critical stability conditions of traffic flow under different vehicle headways are obtained,and a nonlinear analysis method is further used to give a nonlinear analytical result to study how the disturbance propagates in the metastable region.Combined with the theoretical analysis results,the impact of downstream traffic condition information on the stability and phase change of road traffic flow was discussed through numerical simulations.It was found that sharing the information of MHVT can significantly smooth the traffic flow and suppress the formation of traffic congestion.(3)Constructing a microscopic road traffic flow model that can describe the impact of vehicle communication reliability on traffic flow.Considering that the reliability of vehicle communication may have an important impact on the connected vehicle traffic flow system,this paper builds a random microscopic traffic flow following model that can describe the reliability of inter-vehicle communication based on the research content(2).In order to prove the impact of random shared information imperfect connections on traffic flow,this paper uses linear and nonlinear analysis methods to theoretically analyze the model,and further verify the analytical results through numerical experiments in different traffic scenarios.The results show that the influence of the communication reliability between the downstream vehicle and the current vehicle on the stability of the traffic flow is related to the relative position of the downstream vehicle.The closer the relative position of the vehicle is to the current vehicle,the greater the influence on the stability of the traffic flow.