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Chaotic analysis of traffic time series

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  • Shang, Pengjian
  • Li, Xuewei
  • Kamae, Santi

Abstract

In this paper, we applied non-linear time series modeling techniques to analyze the traffic data collected from the Beijing Xizhimen. The results indicated that chaotic characteristics obviously exist in the traffic system; techniques based on phase space dynamics can be used to analyze and predict the traffic speed.

Suggested Citation

  • Shang, Pengjian & Li, Xuewei & Kamae, Santi, 2005. "Chaotic analysis of traffic time series," Chaos, Solitons & Fractals, Elsevier, vol. 25(1), pages 121-128.
    • Handle: RePEc:eee:chsofr:v:25:y:2005:i:1:p:121-128
    DOI: 10.1016/j.chaos.2004.09.104
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    References listed on IDEAS

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    1. Denos C. Gazis & Robert Herman & Richard W. Rothery, 1961. "Nonlinear Follow-the-Leader Models of Traffic Flow," Operations Research, INFORMS, vol. 9(4), pages 545-567, August.
    2. Neil A. Gershenfeld & Andreas S. Weigend, 1993. "The Future of Time Series: Learning and Understanding," Working Papers 93-08-053, Santa Fe Institute.
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    Citations

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    Cited by:

    1. Dai, Meifeng & Zhang, Cheng & Zhang, Danping, 2014. "Multifractal and singularity analysis of highway volume data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 332-340.
    2. Leung, Eunice & Ma, King F. & Xie, Nan, 2023. "Nonlinear modeling of sparkling drink bubbles using a physics informed long short term memory network," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    3. Shang, Du & Xu, Mengjia & Shang, Pengjian, 2017. "Generalized sample entropy analysis for traffic signals based on similarity measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 1-7.
    4. Ayşe İşi & Fatih Çemrek, 2019. "Comparison of the Global, Local and Semi-Local Chaotic Prediction Methods for Stock Markets: The Case of FTSE-100 Index," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 7(2), pages 289-300, December.
    5. Zhuofei Xia & Jiayuan Gong & Hailong Yu & Wenbo Ren & Jingnan Wang, 2022. "Research on Urban Traffic Incident Detection Based on Vehicle Cameras," Future Internet, MDPI, vol. 14(8), pages 1-17, July.
    6. Zhang, Yali & Shang, Pengjian & Sun, Zhenghui, 2018. "Diversity analysis based on ordered patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1126-1133.
    7. Iseri, Müge & Caglar, Hikmet & Caglar, Nazan, 2008. "A model proposal for the chaotic structure of Istanbul stock exchange," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1392-1398.
    8. Yin, Yi & Shang, Pengjian & Ahn, Andrew C. & Peng, Chung-Kang, 2019. "Multiscale joint permutation entropy for complex time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 388-402.
    9. Zhang, Ningning & Lin, Aijing & Ma, Hui & Shang, Pengjian & Yang, Pengbo, 2018. "Weighted multivariate composite multiscale sample entropy analysis for the complexity of nonlinear times series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 595-607.
    10. Inoue, Kei & Tani, Kazuki, 2023. "Quantification of chaos in a time series generated from a traffic flow model using the extended entropic chaos degree," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    11. Shang, Pengjian & Lu, Yongbo & Kamae, Santi, 2008. "Detecting long-range correlations of traffic time series with multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 36(1), pages 82-90.
    12. Xu, Xuefang & Hu, Shiting & Shi, Peiming & Shao, Huaishuang & Li, Ruixiong & Li, Zhi, 2023. "Natural phase space reconstruction-based broad learning system for short-term wind speed prediction: Case studies of an offshore wind farm," Energy, Elsevier, vol. 262(PA).
    13. Li, Xuewei & Shang, Pengjian, 2007. "Multifractal classification of road traffic flows," Chaos, Solitons & Fractals, Elsevier, vol. 31(5), pages 1089-1094.
    14. Lu, Wenqi & Yi, Ziwei & Wu, Renfei & Rui, Yikang & Ran, Bin, 2022. "Traffic speed forecasting for urban roads: A deep ensemble neural network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    15. Yin, Yi & Shang, Pengjian, 2016. "Forecasting traffic time series with multivariate predicting method," Applied Mathematics and Computation, Elsevier, vol. 291(C), pages 266-278.
    16. Xu, Kaiye & Shang, Pengjian & Feng, Guochen, 2015. "Multifractal time series analysis using the improved 0–1 test model," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 134-143.

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