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Quantitative Estimation of Self-Organization in Bi-directional and Crossing Flows During Crowd Movements

In: Traffic and Granular Flow '13

Author

Listed:
  • Dorine C. Duives

    (Delft University of Technology)

  • Winnie Daamen

    (Delft University of Technology)

  • Serge P. Hoogendoorn

    (Delft University of Technology)

Abstract

Understanding emerging phenomena in crowd movements is necessary to understand how pedestrians behave during these movements under different circumstances and over time. Measures able to identify self-organization patterns are currently scarce. In the present study the way in which three measures (the cluster-method (Moussaid, et al. PLoS Comput Biol 8(3):e1002442, 2012), Efficiency (Helbing (1997) Verkehrsdynamik – Neue physikalische Modellierungskonzepte, 1st edn. Springer, Berlin/Heidelberg, p. 46), and Polarization (Hemelrijk and Hildenbrandt, PLoS ONE 6(8):e22479, 2011)) identify the presence of self-organization within crowd movements. Trajectory data sets resulting from a laboratory experiment and several simulations are used as a basis for the assessment. It was found for all three methods that the extent to which self-organization can be accurately predicted depends on the flow situation. Furthermore, two out of three methods were able to detect the presence of self-organization in pedestrian flows at all.

Suggested Citation

  • Dorine C. Duives & Winnie Daamen & Serge P. Hoogendoorn, 2015. "Quantitative Estimation of Self-Organization in Bi-directional and Crossing Flows During Crowd Movements," Springer Books, in: Mohcine Chraibi & Maik Boltes & Andreas Schadschneider & Armin Seyfried (ed.), Traffic and Granular Flow '13, edition 127, pages 251-256, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-10629-8_30
    DOI: 10.1007/978-3-319-10629-8_30
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