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Fractal behavior of traffic volume on urban expressway through adaptive fractal analysis

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  • He, Hong-di
  • Wang, Jun-li
  • Wei, Hai-rui
  • Ye, Cheng
  • Ding, Yi

Abstract

In this paper, we investigate the fractal behavior of traffic volume in urban expressway based on a newly developed adaptive fractal analysis (AFA), which has a number of advantages over traditional method of detrended fluctuation analysis (DFA). Before fractal analysis, autocorrelation function was first adopted on traffic volume data and the long-range correlation behavior was found to be existed in both on-ramp and off-ramp situations. Then AFA as well as DFA was applied to further examine the fractal behavior. The results showed that the multifractality and the long-range anti-persistent behavior existed on both on-ramp and off-ramp. Additionally, multifractal analysis on weekdays and weekends are performed respectively and the results show that the degree of multifractality on weekdays is higher than that on weekends, implying that long-range correlation behaviors were more obvious on weekdays. Finally, the source of multifractality is examined with randomly shuffled and the surrogated series. Long-range correlation behaviors are identified in both on-ramp and off-ramp situations and fat-tail distributions were found to make little in the contributions of multifractality.

Suggested Citation

  • He, Hong-di & Wang, Jun-li & Wei, Hai-rui & Ye, Cheng & Ding, Yi, 2016. "Fractal behavior of traffic volume on urban expressway through adaptive fractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 518-525.
    • Handle: RePEc:eee:phsmap:v:443:y:2016:i:c:p:518-525
    DOI: 10.1016/j.physa.2015.10.004
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    References listed on IDEAS

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    2. Doménech-Carbó, Antonio, 2019. "Rise and fall of historic tram networks: Logistic approximation and discontinuous events," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 315-323.

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