Research On Traffic Adaptability Of Car-Following Behavior Of Connected Vehicles Based On Vehicle-to-Vehicle Communication

With the development of the Internet of vehicles technology,intelligence and networking will become the main characteristics of the future traffic.Under the environment of vehicle-to-vehicle(V2V)communication,the information sharing ability of the connected vehicles(CV)makes their car-following behavior different from human vehicles(HV),and whether the car-following behavior can adapt to the complex road operation environment and improve the efficiency of the traffic system is an urgent problem to be studied.Therefore,it is important to promote the practical application of V2 V technology by studying the car-following behavior of CV under the complex road operation environment and mastering the possible positive and negative effects of V2 V technology on the existing transportation system,so as to promote the practical application of V2 V technology.In this paper,the traffic adaptability of car-following behavior of CV based on V2 V is studied by using in-field data.First of all,based on the review of the research status of car following behavior and adaptability in the traditional environment and V2 V environment,this paper summarizes the shortcomings of the existing research,extends the car following behavior from the theoretical modeling level to the traffic adaptability evaluation level,and gives the research content and technical route of this paper.Secondly,the differences of driving process,car-following behavior characteristics and carfollowing modeling between traditional environment and V2 V environment are compared and analyzed to provide theoretical basis for the follow-up study.Then,the concept of traffic adaptability of car-following behavior is defined,and response time,acceleration change rate,speed variation coefficient,time headway and the reciprocal of collision to time,steady-state transfer time are designed as characterization indicators of traffic adaptability of car-following behaviors,based on these characterization indicators,the evaluation index system of the car-following behavior is proposed,which includes: the average value of response time,the average value of absolute of acceleration variation rate,speed variation coefficient,the average of time headway,the maximum value of reciprocal of collision to time,the mean value of steady-state transition time.At the same time,in order to comprehensively evaluate the traffic adaptability of car following behavior,aiming at the problem that the evaluation results may not be consistent among various evaluation methods,a combined evaluation model of traffic adaptability of car-following behavior based on maximizing deviation is proposed.Three evaluation methods,namely grey clustering analysis,matter-element analysis and fuzzy comprehensive evaluation,are selected to form a combination method set The single evaluation method is used to evaluate the traffic adaptability of car following behavior respectively.For the evaluation method passing Kendall consistency coefficient test,the combination weight of each evaluation method is solved based on the idea of maximizing deviation,and the evaluation results of each method are combined to obtain the combined evaluation result.Then,the car-following test platform based on V2 V is built,and the hardware and software of the test platform are designed.Four scenarios of acceleration,deceleration,stop-start,and forward collision warning are designed,and the in-field data are collected as the data source of the subsequent car-following characterization indicators extraction and combination evaluation.Finally,considering the complex road operation environment factors such as different operation speed,working condition,road grade,weather,service level,etc.,this paper explores the change rule of adaptability indicators under different factors from the perspective of statistics,and analyzes the extent of the traffic adaptability of the car-following behavior of CV under different factors.The combined evaluation value of car following behavior and single evaluation index combination evaluation value are calculated,and the evaluation grade is divided according to the score interval.The analysis results of traffic adaptability characterization index of car-following behavior show that compared with the traditional environment,the average response time of drivers in V2 V environment is shortened by 0.96 s,the average headway is reduced by 27%,the variation rate of acceleration,the reciprocal of collision time and the steadystate transfer time are smaller.Under the influence of different factors,there are some differences in each characterization index,which reflects that the traffic adaptability of car-following behavior of CV is different under different influence factors,that is,reaction ability,comfort,handling stability and safety are different.The combined evaluation results of traffic adaptability of car-following behavior show that the driver's perceived decision-making ability is greatly improved,the handling stability of the vehicle is stronger,and the risk of rear end collision is reduced in most cases.Even though the CV based on V2 V is closer to the car following distance than HV,the traffic adaptability of CV car following behavior is higher than that of HV.