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Wavelet analysis in a traffic model

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  • Huang, Ding-wei

Abstract

Wavelet analysis is applied to the study of vehicular fluctuations in highway traffic. The traffic flow on a single lane highway is simulated by the Nagel–Schreckenberg traffic model. Both the usual correlation functions as well as the wavelet-transformed functions are calculated and compared. Off-diagonal correlations are effectively suppressed by the wavelets, and correlations from different scales are nearly decoupled. The signature of traffic jams is identified in the wavelet-spectrum. Wavelet analysis provides a useful tool to explore the self-similarity in traffic fluctuations.

Suggested Citation

  • Huang, Ding-wei, 2003. "Wavelet analysis in a traffic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 329(1), pages 298-308.
    • Handle: RePEc:eee:phsmap:v:329:y:2003:i:1:p:298-308
    DOI: 10.1016/S0378-4371(03)00623-X
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    Cited by:

    1. Chen, Yuting & Mao, Jiannan & Zhang, Zhao & Huang, Hao & Lu, Weike & Yan, Qipeng & Liu, Lan, 2022. "A quasi-contagion process modeling and characteristic analysis for real-world urban traffic network congestion patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    2. Tang, Jinjun & Chen, Xinqiang & Hu, Zheng & Zong, Fang & Han, Chunyang & Li, Leixiao, 2019. "Traffic flow prediction based on combination of support vector machine and data denoising schemes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    3. Chen, Mu-Chen & Wei, Yu, 2011. "Exploring time variants for short-term passenger flow," Journal of Transport Geography, Elsevier, vol. 19(4), pages 488-498.

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