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Investigating the Effect of Social Groups in Uni-directional Pedestrian Flow

  • Luca Crociani
  • Yiping ZengEmail author
  • Andrea Gorrini
  • Giuseppe Vizzari
  • Weiguo Song
Conference paper

Abstract

The influence of cohesion among members of dyads is investigated in scenarios characterized by uni-directional flow by means of a discrete model: a corridor and the egress from a room with a bottleneck of varying width are simulated. The model manages the dynamics of simulated group members with an adaptive mechanism, balancing the probability of movement according to the dispersion of the group; the cohesion mechanism is calibrated through the parameters κc and δ. All scenarios are simulated with two procedures: (Proc. 1) population composed of individual pedestrians, in order to validate the simulation model and to provide baseline data; (Proc. 2) population including dyads (50% of the simulated pedestrians), in order to verify their impact. In the corridor scenario, the presence of dyads causes a reduction of the velocities and specific flow at medium-high densities. Egress from a square room with a unique central exit produces results in line with recent studies in the literature, but also shows that the dyads negatively affect the dynamics, leading generally to a slower walking speed and a lower pedestrian flow. Ignoring the presence of dyads would lead to an overestimation of egress flows.

Notes

Acknowledgements

This research has been supported by the Key Research and Development Program (2016YFC0802508), the Program of Shanghai Science and Technology Committee (16DZ1200106), the Specialized Research Fund for the Doctoral Program of Higher Education of China (20133402110009), the China Scholarship Council (CSC) and Fundamental Research Funds for the Central Universities (WK2320000035).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Luca Crociani
    • 1
  • Yiping Zeng
    • 2
    Email author
  • Andrea Gorrini
    • 1
  • Giuseppe Vizzari
    • 1
  • Weiguo Song
    • 2
  1. 1.CSAI Research CenterUniversity of Milano-BicoccaMilanoItaly
  2. 2.State Key Laboratory of Fire ScienceUniversity of Science and Technology of ChinaHefeiChina

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