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Recurrence analysis of urban traffic congestion index on multi-scale

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  • Wu, Jiaxin
  • Zhou, Xubing
  • Peng, Yi
  • Zhao, Xiaojun

Abstract

As for the increasing traffic pressure in urban cities, it is of great significance to analyze the complex traffic system and grasp the recurrence characteristics of traffic state to better solve the problem of traffic congestion. This paper combines the multi-scale theory and recurrence analysis, which carries out the qualitative and quantitative multi-scale recurrence analysis of the traffic congestion index (TCI) in a period of time in Beijing, China, and further, analyzes the recurrence state of each day in a week, as well as mines the recurrence law. The empirical results reveal that the low-frequency components of the dynamic characteristics of TCI play a major role in the long-term traffic state prediction. The traffic state between weekdays and weekends tends to change, and the state on weekdays is more regular, whereas on Friday, as the critical day for rest days, it is more complex and random. The conclusion of this paper will play a fundamental role in grasping the essential law of Beijing’s traffic system and analyzing the traffic congestion problem and the urban traffic system, which has strong practical significance.

Suggested Citation

  • Wu, Jiaxin & Zhou, Xubing & Peng, Yi & Zhao, Xiaojun, 2022. "Recurrence analysis of urban traffic congestion index on multi-scale," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    • Handle: RePEc:eee:phsmap:v:585:y:2022:i:c:s0378437121007123
    DOI: 10.1016/j.physa.2021.126439
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    References listed on IDEAS

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