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Traffic speed cloud maps: A new method for analyzing macroscopic traffic flow

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  • Xiao, Jianli
  • Wang, Zhonghao

Abstract

Among traffic flow analysis, there are many methods presented for microscopic and mesoscopic traffic flow in past decades. However, the methods for macroscopic traffic flow analysis are relatively few. That is because the macroscopic traffic flow analysis needs more data and computational resources. In this paper, we focus on macroscopic traffic flow analysis using massive traffic data. A new method, traffic speed cloud maps, is proposed. It can present the traffic states in a large scale, accurately. Also, it can describe the variations of the congestion area. More importantly, with traffic speed cloud maps, people can capture the forming and degrading processes of the congestion and investigate the operation rules of macroscopic traffic flow. In order to evaluate the effectiveness of traffic speed cloud maps, 14 786 073 traffic samples are taken to perform experiments. Experimental results show that traffic speed cloud maps can present the traffic state of large areas accurately, and help us to investigate the variation of macroscopic traffic flow states intuitively and efficiently.

Suggested Citation

  • Xiao, Jianli & Wang, Zhonghao, 2018. "Traffic speed cloud maps: A new method for analyzing macroscopic traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 367-375.
    • Handle: RePEc:eee:phsmap:v:508:y:2018:i:c:p:367-375
    DOI: 10.1016/j.physa.2018.05.122
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    References listed on IDEAS

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    1. Rajat Jain & J. Macgregor Smith, 1997. "Modeling Vehicular Traffic Flow using M/G/C/C State Dependent Queueing Models," Transportation Science, INFORMS, vol. 31(4), pages 324-336, November.
    2. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    3. Paul Wasielewski, 1979. "Car-Following Headways on Freeways Interpreted by the Semi-Poisson Headway Distribution Model," Transportation Science, INFORMS, vol. 13(1), pages 36-55, February.
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    Cited by:

    1. Mondal, Satyajit & Gupta, Ankit, 2021. "Speed distribution for interrupted flow facility under mixed traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    2. Hu, Xu & Li, Dongshuang & Yu, Zhaoyuan & Yan, Zhenjun & Luo, Wen & Yuan, Linwang, 2022. "Quantum harmonic oscillator model for fine-grained expressway traffic volume simulation considering individual heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).

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