Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of ‘stripe’ formation in human data

Author:

Mullick PratikORCID,Fontaine Sylvain,Appert-Rolland CécileORCID,Olivier Anne-HélèneORCID,Warren William H.ORCID,Pettré Julien

Abstract

When two streams of pedestrians cross at an angle, striped patterns spontaneously emerge as a result of local pedestrian interactions. This clear case of self-organized pattern formation remains to be elucidated. In counterflows, with a crossing angle of 180°, alternating lanes of traffic are commonly observed moving in opposite directions, whereas in crossing flows at an angle of 90°, diagonal stripes have been reported. Naka (1977) hypothesized that stripe orientation is perpendicular to the bisector of the crossing angle. However, studies of crossing flows at acute and obtuse angles remain underdeveloped. We tested the bisector hypothesis in experiments on small groups (18-19 participants each) crossing at seven angles (30° intervals), and analyzed the geometric properties of stripes. We present two novel computational methods for analyzing striped patterns in pedestrian data: (i) an edge-cutting algorithm, which detects the dynamic formation of stripes and allows us to measure local properties of individual stripes; and (ii) a pattern-matching technique, based on the Gabor function, which allows us to estimate global properties (orientation and wavelength) of the striped pattern at a time T. We find an invariant property: stripes in the two groups are parallel and perpendicular to the bisector at all crossing angles. In contrast, other properties depend on the crossing angle: stripe spacing (wavelength), stripe size (number of pedestrians per stripe), and crossing time all decrease as the crossing angle increases from 30° to 180°, whereas the number of stripes increases with crossing angle. We also observe that the width of individual stripes is dynamically squeezed as the two groups cross each other. The findings thus support the bisector hypothesis at a wide range of crossing angles, although the theoretical reasons for this invariant remain unclear. The present results provide empirical constraints on theoretical studies and computational models of crossing flows.

Funder

Agence de l’eau Loire-Bretagne

Investissements d’Avenir

Publisher

Public Library of Science (PLoS)

Subject

Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics

Reference79 articles.

1. Collective effects in traffic on bi-directional ant trails;A John;2004 J Theor Biol,2004

2. Deciphering Interactions in Moving Animal Groups;J Gautrais;PLoS Comput Biol,2012

3. Traffic Instabilities in Self-Organized Pedestrian Crowds;M Moussaïd;PLoS Comput Biol,2012

4. Individual Rules for Trail Pattern Formation in Argentine Ants (Linepithema humile);A Perna;PLOS Comput Biol,2012

5. Prediction and classification in equation-free collective motion dynamics;K Fujii;PLOS Comput Biol,2018

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