Evidence map›Paper›PMID 35679329›Full record

ArticlePLoS computational biology2022

Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of 'stripe' formation in human data.

Pratik Mullick, Sylvain Fontaine, Cécile Appert-Rolland, Anne-Hélène Olivier, William H Warren, Julien Pettré

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Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Human Crowds as Social Networks: Collective Dynamics of Consensus and Polarization.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Pratik MullickINRIA Rennes - Bretagne Atlantique, Campus de Beaulieu, Rennes, France.ORCID 0000-0003-0133-0354
Sylvain FontaineUniversité Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France.
Cécile Appert-RollandUniversité Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France.ORCID 0000-0002-0985-6230
Anne-Hélène OlivierUniversité Rennes, INRIA, CNRS, IRISA, M2S, Rennes, France.ORCID 0000-0002-2833-020X
William H WarrenDepartment of Cognitive, Linguistic and Psychological Sciences, Brown University, Providence, Rhode Island, United States of America.ORCID 0000-0003-4843-2315
Julien PettréINRIA Rennes - Bretagne Atlantique, Campus de Beaulieu, Rennes, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

PedestriansAlgorithmsHumansModels, Theoretical

Identifiers

PMID35679329
PMCPMC9216623

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.