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

摘要

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 dynamicsare still lacking a systematic individual-level experimental verification, and the local mechanismsunderlying the formation of collective patterns are not yet known in detail. We have conducted a set ofwell-controlled experiments with pedestrians performing simple avoidance tasks in order to determine thelaws ruling their behaviour during interactions. The analysis of the large trajectory dataset was used tocompute a behavioural map that describes the average change of the direction and speed of a pedestrian forvarious interaction distances and angles. The experimental results reveal features of the decision processwhen pedestrians choose the side on which they evade, and show a side preference that is amplified bymutual interactions. The predictions of a binary interaction model based on the above findings were thencompared with bidirectional flows of people recorded in a crowded street. Simulations generate twoasymmetric lanes with opposite directions of motion, in quantitative agreement with our empiricalobservations. The knowledge of pedestrian behavioural laws is an important step ahead in theunderstanding of the underlying dynamics of crowd behaviour and allows for reliable predictions ofcollective pedestrian movements under natural conditions.