Research On Modeling Of Heterogeneous Microscopic Traffic Flow

With the deep integration of intelligent transportation system and internet of vehicles technology,the Connected and Autonomous Vehicle(CAV)in the Intelligent network environment has emerged as the times require.The mixed driving of CAV and Human-Driven Vehicle(HDV)on the road forms a heterogeneous traffic flow.Due to the change of the information interaction mode,the vehicle following model in the traditional environment cannot be fully applied to the new heterogeneous traffic.streaming environment.Based on this,this paper takes heterogeneous traffic flow as the research object,draws on the existing car following model,constructs a vehicle following model in the intelligent network environment,and uses the genetic algorithm to optimize the parameters of the model,and finally explores through numerical simulation.The effect of CAV on the flow capacity of heterogeneous traffic flow under different permeability conditions was investigated.The main work of the paper is as follows:First of all,on the basis of consulting relevant literatures at home and abroad,the research background and significance,and the current research status at home and abroad are comprehensively reviewed.By analyzing the research status of road capacity,traffic flow model construction,and traffic flow model stability,the shortcomings of existing research are summarized,and the research purpose and content of the paper are determined according to the research shortcomings.The overall framework lays the theoretical foundation and methods.Secondly,the paper determines the optimal speed model as the artificial driving model in the heterogeneous traffic flow model;comprehensively considers factors such as sensor sensitivity coefficient,forward and backward coordinated optimal speed,multiple preceding vehicles and the speed difference between adjacent rear vehicles.After that,a vehicle following model in an intelligent networked environment was constructed,and the critical stability conditions of the model were solved by the linear stability analysis method,and numerical simulation analysis was carried out at the same time;then the "NGSIM" open source data was selected as the basis for model parameter calibration.The data is preprocessed by threshold method and comparative analysis method,and a genetic algorithm is designed to complete the calibration of model parameters.Finally,in order to explore the influence of CAV on the flow capacity of heterogeneous traffic flow under different permeability conditions,the paper establishes the flow-density expression under the environment of heterogeneous traffic flow,and uses computer simulation to verify it.Sensitivity analysis was carried out on the parameters of flow capacity.After simulation verification and analysis,the model constructed in this paper has high stability,and with the increase of CAV penetration rate,the road capacity is improved accordingly.After simulation verification and analysis,the constructed heterogeneous microscopic traffic flow model can better describe the influence of CAV and HDV on the whole mixed traffic flow under mixed traffic conditions,and the mixed traffic flow capacity is gradually increasing with the increase of CAV penetration.