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

TL;DR

This study experimentally investigates how individual pedestrian interactions lead to self-organized collective patterns, revealing behavioral rules and side preferences that explain lane formation in crowds.

Contribution

It provides the first systematic experimental verification of individual-level behaviors underlying crowd self-organization and develops a predictive binary interaction model.

Findings

Pedestrians show a side preference during avoidance that is amplified by interactions.

The behavioral map quantifies how direction and speed change with interaction parameters.

Simulations based on the model reproduce asymmetric lane formation observed in real crowds.

Abstract

In animal societies as well as in human crowds, many observed collective behaviours result from self-organized processes based on local interactions among individuals. However, models of crowd dynamics are still lacking a systematic individual-level experimental verification, and the local mechanisms underlying the formation of collective patterns are not yet known in detail. We have conducted a set of well-controlled experiments with pedestrians performing simple avoidance tasks in order to determine the laws ruling their behaviour during interactions. The analysis of the large trajectory dataset was used to compute a behavioural map that describes the average change of the direction and speed of a pedestrian for various interaction distances and angles. The experimental results reveal features of the decision process when pedestrians choose the side on which they evade, and show a side preference that is amplified by mutual interactions. The predictions of a binary interaction model based on the above findings were then compared to bidirectional flows of people recorded in a crowded street. Simulations generate two asymmetric lanes with opposite directions of motion, in quantitative agreement with our empirical observations. The knowledge of pedestrian behavioural laws is an important step ahead in the understanding of the underlying dynamics of crowd behaviour and allows for reliable predictions of collective pedestrian movements under natural conditions.