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Detection of Steady State in Pedestrian Experiments

In: Traffic and Granular Flow '15

Author

Listed:
  • Weichen Liao

    (Beijing University of Chemical Technology
    Forschungszentrum Jülich GmbH)

  • Antoine Tordeux

    (Forschungszentrum Jülich GmbH
    Bergische Universität Wuppertal)

  • Armin Seyfried

    (Forschungszentrum Jülich GmbH)

  • Mohcine Chraibi

    (Forschungszentrum Jülich GmbH)

  • Xiaoping Zheng

    (Tsinghua University)

  • Ying Zhao

    (Beijing University of Chemical Technology)

Abstract

Initial conditionsLiao, Weichen could have strong influencesTordeux, Antoine on the dynamics of pedestrianSeyfried, Armin experiments. Thus, a carefulChraibi, Mohcine differentiation between transientZheng, Xiaoping state and steady state is important and necessary for a thoroughZhao, Ying study. In this contribution a modified CUSUM algorithm is proposed to automatically detect steady state from time series of pedestrian experiments. Major modifications on the statistics include introducing a step function to enhance the sensitivity, adding a boundary to limit the increase, and simplifying the calculation to improve the computational efficiency. Furthermore, the threshold of the detection parameter is calibrated using an autoregressive process. By testing the robustness, the modified CUSUM algorithm is able to reproduce identical steady state with different references. Its application well contributes to accurate analysis and reliable comparison of experimental results.

Suggested Citation

  • Weichen Liao & Antoine Tordeux & Armin Seyfried & Mohcine Chraibi & Xiaoping Zheng & Ying Zhao, 2016. "Detection of Steady State in Pedestrian Experiments," Springer Books, in: Victor L. Knoop & Winnie Daamen (ed.), Traffic and Granular Flow '15, pages 73-79, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-33482-0_10
    DOI: 10.1007/978-3-319-33482-0_10
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