Literature DB >> 17995058

Modeling crowd turbulence by many-particle simulations.

Wenjian Yu1, Anders Johansson.   

Abstract

A recent study [D. Helbing, A. Johansson, and H. Z. Al-Abideen, Phys. Rev. E 75, 046109 (2007)] has revealed a "turbulent" state of pedestrian flows, which is characterized by sudden displacements and causes the falling and trampling of people. However, turbulent crowd motion is not reproduced well by current many-particle models due to their insufficient representation of the local interactions in areas of extreme densities. In this contribution, we extend the repulsive force term of the social force model to reproduce crowd turbulence. We perform numerical simulations of pedestrians moving through a bottleneck area with this model. The transitions from laminar to stop-and-go and turbulent flows are observed. The empirical features characterizing crowd turbulence, such as the structure function and the probability density function of velocity increments, are reproduced well; i.e., they are well compatible with an analysis of video data during the annual Muslim pilgrimage.

Entities:  

Year:  2007        PMID: 17995058     DOI: 10.1103/PhysRevE.76.046105

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  11 in total

1.  How simple rules determine pedestrian behavior and crowd disasters.

Authors:  Mehdi Moussaïd; Dirk Helbing; Guy Theraulaz
Journal:  Proc Natl Acad Sci U S A       Date:  2011-04-18       Impact factor: 11.205

2.  The walking behaviour of pedestrian social groups and its impact on crowd dynamics.

Authors:  Mehdi Moussaïd; Niriaska Perozo; Simon Garnier; Dirk Helbing; Guy Theraulaz
Journal:  PLoS One       Date:  2010-04-07       Impact factor: 3.240

3.  Experimental study of the behavioural mechanisms underlying self-organization in human crowds.

Authors:  Mehdi Moussaïd; Dirk Helbing; Simon Garnier; Anders Johansson; Maud Combe; Guy Theraulaz
Journal:  Proc Biol Sci       Date:  2009-05-13       Impact factor: 5.349

4.  Efficient egress of escaping ants stressed with temperature.

Authors:  Santiago Boari; Roxana Josens; Daniel R Parisi
Journal:  PLoS One       Date:  2013-11-29       Impact factor: 3.240

5.  Predicting pedestrian flow: a methodology and a proof of concept based on real-life data.

Authors:  Maria Davidich; Gerta Köster
Journal:  PLoS One       Date:  2013-12-27       Impact factor: 3.240

6.  Analytical modelling of the spread of disease in confined and crowded spaces.

Authors:  Lara Goscé; David A W Barton; Anders Johansson
Journal:  Sci Rep       Date:  2014-05-06       Impact factor: 4.379

7.  Evacuation of Pedestrians with Two Motion Modes for Panic System.

Authors:  You Zou; Jiarong Xie; Binghong Wang
Journal:  PLoS One       Date:  2016-04-07       Impact factor: 3.240

8.  From Mindless Masses to Small Groups: Conceptualizing Collective Behavior in Crowd Modeling.

Authors:  Anne Templeton; John Drury; Andrew Philippides
Journal:  Rev Gen Psychol       Date:  2015-08-17

9.  Effects of Switching Behavior for the Attraction on Pedestrian Dynamics.

Authors:  Jaeyoung Kwak; Hang-Hyun Jo; Tapio Luttinen; Iisakki Kosonen
Journal:  PLoS One       Date:  2015-07-28       Impact factor: 3.240

10.  Pedestrian collective motion in competitive room evacuation.

Authors:  A Garcimartín; J M Pastor; C Martín-Gómez; D Parisi; I Zuriguel
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

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