4.6 Article

Stability analysis and the fundamental diagram for mixed connected automated and human-driven vehicles

Journal

Publisher

ELSEVIER
DOI: 10.1016/j.physa.2019.121931

Keywords

Mixed traffic flow; Fundamental diagram; Car-following; Connected automated vehicles; Stability; Penetration rates

Funding

  1. Open Fund Project of Chongqing Key Laboratory of Traffic and Transportation, China [2018TE01]
  2. National Science Foundation of China [5157765, 61703064, 71771190]
  3. Chengdu Science and Technology Bureau, China [2017-RK00-00362-ZE]
  4. Chongqing Research Program of Basic Research and Frontier Technology, China [cstc2017jcyjAX0473]
  5. Southwest Jiaotong University Graduate Academic Training and Promotion Program, China [2019KCJS46]
  6. Education Department of Hunan Province, China [16B008]

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With the development of connected automated vehicles (CAVs), traffic flow on the road is generally mixed with human-driven vehicles (HDVs) and CAVs. In this paper, the full velocity difference (FVD) model and cooperative adaptive cruise control (CACC) model validated by PATH laboratory of University of California, Berkeley, are used to describe the car-following (CF) driving behavior of HDVs and CAVs, respectively. Firstly, an analytical method for the stability of mixed traffic flow is developed and the stability conditions under different penetration rates of CAVs are obtained. Then, the fundamental diagram model of mixed traffic flow under different penetration rates is derived and the influence factors of the fundamental diagram are analyzed. Finally, a simulation experiment is designed to verify the effectiveness of the proposed model. The simulation results show that there are some differences between the simulation data and the theoretical results under different penetration rates. The simulation data are fluctuating, but they are both on the theoretical curve. The overall trend is consistent with the theoretical results, which proves the validity of the fundamental diagram analysis results. (C) 2019 Elsevier B.V. All rights reserved.

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