Citation

Cordes J, Schadschneider A, Nicolas A. PNAS Nexus 2024; 3(4): pgae120.

Copyright

(Copyright © 2024, National Academy of Sciences (USA), Publisher Oxford University Press)

DOI

10.1093/pnasnexus/pgae120

PMID

38577258

PMCID

PMC10994203

Abstract

In fluid mechanics, dimensionless numbers like the Reynolds number help classify flows. We argue that such a classification is also relevant for crowd flows by putting forward the dimensionless Intrusion and Avoidance numbers, which quantify the intrusions into the pedestrians' personal spaces and the imminency of the collisions that they face, respectively. Using an extensive dataset, we show that these numbers delineate regimes where distinct variables characterize the crowd's arrangement, namely, Euclidean distances at low Avoidance number and times-to-collision at low Intrusion number. On the basis of these findings, a perturbative expansion of the individual pedestrian dynamics is carried out around the noninteracting state, in quite general terms. Simulations confirm that this expansion performs well in its expected regime of applicability.

Language: en