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      Inflow Process of Pedestrians to a Confined Space

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          Abstract

          To better design safe and comfortable urban spaces, understanding the nature of human crowd movement is important. However, precise interactions among pedestrians are difficult to measure in the presence of their complex decision-making processes and many related factors. While extensive studies on pedestrian flow through bottlenecks and corridors have been conducted, the dominant mode of interaction in these scenarios may not be relevant in different scenarios. Here, we attempt to decipher the factors that affect human reactions to other individuals from a different perspective. We conducted experiments employing the inflow process in which pedestrians successively enter a confined area (like an elevator) and look for a temporary position. In this process, pedestrians have a wider range of options regarding their motion than in the classical scenarios; therefore, other factors might become relevant. The preference of location is visualized by pedestrian density profiles obtained from recorded pedestrian trajectories. Non-trivial patterns of space acquisition, e.g., an apparent preference for positions near corners, were observed. This indicates the relevance of psychological and anticipative factors beyond the private sphere, which have not been deeply discussed so far in the literature on pedestrian dynamics. From the results, four major factors, which we call flow avoidance, distance cost, angle cost, and boundary preference, were suggested. We confirmed that a description of decision-making based on these factors can give a rise to realistic preference patterns, using a simple mathematical model. Our findings provide new perspectives and a baseline for considering the optimization of design and safety in crowded public areas and public transport carriers.

          Author and article information

          Journal
          Collective Dynamics
          Coll Dyn
          Forschungszentrum Julich, Zentralbibliothek
          2366-8539
          March 15 2016
          July 28 2016
          : 1
          :
          Article
          10.17815/CD.2016.4
          65379379-95c9-4a15-aaae-32b25436ef3a
          © 2016

          http://creativecommons.org/licenses/by/4.0

          History

          Applied mathematics,Applied computer science,Civil engineering,Social & Behavioral Sciences,Data analysis,Nonlinear & Complex systems

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