Research On Freeway Car-following Modeling And Simulation In Connected Vehicle Environment

With the rapid development of social economy and urban motorization,a series of problems emerged,such as traffic safety,traffic congestion and environmental pollution.Freeway is shouldering the responsibility to traffic flow between different areas and regions.Recently,the imbalance between demand and supply of freeway is more significant.The technology of Intelligent Transportation System(ITS)has been attracting more and more attention for its benefits in reducing traffic congestion,pollution,improving traffic efficiency and reducing traffic accidents.Connected Vehicle Technology is one of the core contents in ITS fields.Based on the environment of connected vehicles,the communication mode of vehicles,infrastructures and human beings.Driving behaviors and car-following behaviors will be changed.Adaptive Cruise Control(ACC)and Cooperative Adaptive Cruise Control(CACC)models have received increased attention in recent years,with the advance in Connected and Autonomous Vehicle technologies.The focus of this paper is connected vehicles.With the emergence of Connected and Autonomous Vehicle technologies in recent years,the implementation of the CACC technologies becomes feasible on a large scale.Connected vehicles can affect the driving behaviours characteristics,(1)We can get more real-time and exact traffic information through the wireless between vehicles.Those information can be used in aided driving.(2)The influence of connected vehicles can make forward control contribution and backward control contribution.This paper proposed a multi-class multi-mode car-following model(MMCF)by comparing the stage characteristics of connected vehicles with ACC controller characteristics and CACC controller characteristics.Warning index(w)and time to collision(TTC)are chosen as two judge index to divide the car-following conditions of adaptive cruise control vehicles.Each car-following condition has its acceleration control mode.A MMCF model can be built with this approach.To account for different car-following behaviors in reality,four different car-following models,General Motors(GM),Bando,Gipps,and Intelligent Drive Model(IDM)are calibrated with the same NGSIM dataset.Numerical results obtained that this MMCF model can fit the real data well and has significant advantages by comparing with those four car-following models mentioned above.This study focuses on the development and evaluation of the adaptive control model for the leading vehicle in an ACC/CACC platoon in mixed traffic flow.Bi-directional Control Framework for Leading Vehicle of CACC Vehicle Platoon is proposed in this paper.Two LCACC models are developed based on different assumption and objective function in this paper.The novel Lead-vehicle CACC(LCACC)is derived by solving the minimization problem of reaction acceleration from the following vehicles in the CACC platoon.To evaluate the characteristics of the proposed model,a ring-road stability analysis environment is established by using field trajectory data from NGSIM(Next Generation SIMulation)project as an initial condition.The evaluation consists of a mixed of CACC and regular vehicles.Several model and CACC configuration scenarios are evaluated.For CACC fleet size,we evaluate 3-vehicle,5-vehicle,10-vehicle,15-vehicle and 20-vehicle platoon respectively.Car-following models evaluated include GM,Bando,Gipps,and IDM model.The objective function of the proposed LCACC model is a function of the total deviation of all CACC vehicles with respect to the design clearance.To avoid introducing additional impact such as lane-change and merging,the ring-road analysis takes the initial vehicle states from the snapshot at a particular time of all vehicles on one lane in field trajectory data from NGSIM(Next Generation SIMulation)project as an initial condition.The ring-road experiment is executed for 30 times to accumulate enough measurement regarding the stability impact.A mathematical analysis(frequency-transformation)and a numerical simulation(Ring road test)are used to analyze the stability of the LCACC models established in the paper.