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.
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Duives, D.C., Daamen, W., Hoogendoorn, S.P. (2015). Quantitative Estimation of Self-Organization in Bi-directional and Crossing Flows During Crowd Movements. In: Chraibi, M., Boltes, M., Schadschneider, A., Seyfried, A. (eds) Traffic and Granular Flow '13. Springer, Cham. https://doi.org/10.1007/978-3-319-10629-8_30
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DOI: https://doi.org/10.1007/978-3-319-10629-8_30
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