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Congestions and spectral transitions in time-lagged correlations of motorway traffic

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  • Hollbeck, Gabor B.
  • Pilarczyk, René
  • Wang, Shanshan
  • Schreckenberg, Michael
  • Guhr, Thomas

Abstract

The understanding of congestions contributes to the development of effective traffic management strategies. The propagation of congestions from a motorway section to the neighboring ones results in correlations. Here, we study symmetrized time-lagged correlation matrices and show how their spectral properties reveal congestion durations. We first carry out an empirical analysis of velocities for two local motorway networks, then set up a numerical simulation for indicator time series of traffic phases, and further propose a simplified, analytical model capturing various scenarios of congestion durations. Our empirical analysis reveals a transition behavior for the dominant eigenvalue as function of time lags, reflecting changes in traffic dynamics. Furthermore, both the numerical simulations and the analytical model disclose a nonlinear relation between the spectral transition and the congestion duration.

Suggested Citation

  • Hollbeck, Gabor B. & Pilarczyk, René & Wang, Shanshan & Schreckenberg, Michael & Guhr, Thomas, 2024. "Congestions and spectral transitions in time-lagged correlations of motorway traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 649(C).
  • Handle: RePEc:eee:phsmap:v:649:y:2024:i:c:s0378437124004618
    DOI: 10.1016/j.physa.2024.129952
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    References listed on IDEAS

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    1. Linyin Cheng & Amir AghaKouchak & Eric Gilleland & Richard Katz, 2014. "Non-stationary extreme value analysis in a changing climate," Climatic Change, Springer, vol. 127(2), pages 353-369, November.
    2. Saeedmanesh, Mohammadreza & Geroliminis, Nikolas, 2017. "Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 193-211.
    3. Junqing Tang & Hans Rudolf Heinimann, 2018. "A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-22, January.
    4. Yuriy Stepanov & Philip Rinn & Thomas Guhr & Joachim Peinke & Rudi Schafer, 2015. "Stability and Hierarchy of Quasi-Stationary States: Financial Markets as an Example," Papers 1503.00556, arXiv.org.
    5. Michael C. Munnix & Takashi Shimada & Rudi Schafer & Francois Leyvraz Thomas H. Seligman & Thomas Guhr & H. E. Stanley, 2012. "Identifying States of a Financial Market," Papers 1202.1623, arXiv.org.
    6. Martin Fellendorf & Peter Vortisch, 2010. "Microscopic Traffic Flow Simulator VISSIM," International Series in Operations Research & Management Science, in: Jaume Barceló (ed.), Fundamentals of Traffic Simulation, chapter 0, pages 63-93, Springer.
    7. Dong-Ming Song & Michele Tumminello & Wei-Xing Zhou & Rosario N. Mantegna, 2011. "Evolution of worldwide stock markets, correlation structure and correlation based graphs," Papers 1103.5555, arXiv.org.
    8. Tanzina Afrin & Nita Yodo, 2020. "A Survey of Road Traffic Congestion Measures towards a Sustainable and Resilient Transportation System," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    9. Tenny Lam & Richard Rothery, 1970. "The Spectral Analysis of Speed Fluctuations on a Freeway," Transportation Science, INFORMS, vol. 4(3), pages 293-310, August.
    10. Gartzke, Sebastian & Wang, Shanshan & Guhr, Thomas & Schreckenberg, Michael, 2022. "Spatial correlation analysis of traffic flow on parallel motorways in Germany," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    11. Wang, Shanshan & Schreckenberg, Michael & Guhr, Thomas, 2023. "Response functions as a new concept to study local dynamics in traffic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    12. Burstedde, C & Klauck, K & Schadschneider, A & Zittartz, J, 2001. "Simulation of pedestrian dynamics using a two-dimensional cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 507-525.
    13. Meead Saberi & Homayoun Hamedmoghadam & Mudabber Ashfaq & Seyed Amir Hosseini & Ziyuan Gu & Sajjad Shafiei & Divya J. Nair & Vinayak Dixit & Lauren Gardner & S. Travis Waller & Marta C. González, 2020. "A simple contagion process describes spreading of traffic jams in urban networks," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
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