Cell transmission model of mixed traffic flow of manual–automated driving

QIN Yan-yan1 ZHANG Jian2 CHEN Ling-zhi1 LI Shu-qing1 HE Zhao-yi1 RAN Bin3

(1.School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing, China 400074)
(2.School of Transportation, Southeast University, Nanjing, Jiangsu Province, China 210096)
(3.Department of Civil and Environment Engineering, University of Wisconsin-Madison, Madison WI 53706, Wisconsin, USA)

【Abstract】In order to analyze the impacts of automated driving vehicles on the macroscopic traffic flow characteristics, the mixed traffic flow with manual driving vehicles and automated driving vehicles was considered as the study objective, and the cell transmission model (CTM) of mixed traffic flow with different proportions of automated driving vehicles was proposed. The car-following model proposed by Newell was used for the car-following model of manual driving vehicles, while the model calibrated by PATH program used the real vehicle experiments was employed for the car-following model of automated driving vehicles. The functional relation of equilibrium space headway–speed was calculated according to the car-following models of manual and automated driving vehicles. The fundamental diagram model of mixed traffic flow was derived with different proportions of automated driving vehicles. In addition, the characteristic quantities such as the maximum volume, the maximum jam density, and backward wave speed were calculated for the mixed traffic flow with different proportions of automated driving vehicles. Based on the CTM theory of homogenous traffic flow, the CTM of mixed traffic flow was proposed with different proportions of automated driving vehicles. The moving bottleneck problem was selected for example analysis, the influence time of moving bottleneck with different proportions of automated driving vehicles was calculated by using the mixed traffic flow CTM. The car-following models were used for the microcosmic numerical simulation on the moving bottleneck. The errors between the calculation results of the mixed traffic flow CTM and the microcosmic simulation results of car-following models were analyzed. The accuracy of mixed traffic flow CTM was validated. Research results show that the proposed mixed traffic flow CTM can effectively calculate the influence time of the moving bottleneck. With different proportions of automated driving vehicles, the errors between the calculation results of the mixed traffic flow CTM and the microcosmic simulation results of car-following models are all below 52 s, and the relative errors are all below 10%, which indicates the accuracy of the proposed mixed traffic flow CTM in actual application. The mixed traffic flow CTM reflects the study idea from microcosmic to macroscopic. There are relationships between the microcosmic car-following models and the small-scale automated driving vehicle experiments being gradually implemented. The mixed traffic flow CTM can truthfully reflect the evolutionary process of mixed traffic flow on a single lane in the context of automated driving with different proportions in the future, which enhances the application value of the model research.

【Keywords】 traffic flow; cell transmission model; automated driving; moving bottleneck; influence time;

【DOI】

【Funds】 National Key R&D Program of China (2018YFB1601000, 2016YFB0100906) Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN201900730) Fundamental Research Funds for the Central Universities of Ministry of Education of China (2242020R40045)

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This Article

ISSN:1671-1637

CN: 61-1369/U

Vol 20, No. 02, Pages 229-238

April 2020

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Article Outline

Abstract

  • 0 Introduction
  • 1 Microcosmic car-following model
  • 2 Cell transmission model
  • 3 Example analysis
  • 4 Conclusions
  • References