The effect of perception anisotropy on particle systems describing pedestrian flows in corridors

TL;DR

This paper introduces a microscopic particle-based model to study how perception anisotropy influences pedestrian crowd behavior in corridors, using simulations and characteristic indices to analyze organization and clustering effects.

Contribution

It models perception anisotropy in pedestrian dynamics through a Newton-like system, providing a novel simulation framework to analyze its impact on crowd behavior.

Findings

Perception anisotropy affects crowd organization and clustering.

Simulation indices reveal changes in polarization and clustering due to anisotropy.

Model demonstrates potential for studying pedestrian flow dynamics.

Abstract

We consider a microscopic model (a system of self-propelled particles) to study the behaviour of a large group of pedestrians walking in a corridor. Our point of interest is the effect of anisotropic interactions on the global behaviour of the crowd. The anisotropy we have in mind reflects the fact that people do not perceive (i.e. see, hear, feel or smell) their environment equally well in all directions. The dynamics of the individuals in our model follow from a system of Newton-like equations in the overdamped limit. The instantaneous velocity is modelled in such a way that it accounts for the angle under which an individual perceives another individual. We investigate the effects of this perception anisotropy by means of simulations, very much in the spirit of molecular dynamics. We define a number of characteristic quantifiers (including the polarization index and Morisita index) that serve as measures for e.g. organization and clustering, and we use these indices to investigate the influence of anisotropy on the global behaviour of the crowd. The goal of the paper is to investigate the potentiality of this model; extensive statistical analysis of simulation data, or reproducing any specific real-life situation are beyond its scope.