Fluctuations in pedestrian dynamics routing choices

TL;DR

This study investigates how pedestrians choose routes in complex environments, revealing that collective discomfort and individual fluctuations significantly influence traffic patterns, which often deviate from optimal flow configurations.

Contribution

The paper introduces a collective discomfort function to model pedestrian routing choices and highlights the importance of individual fluctuations in macroscopic traffic flow analysis.

Findings

Traffic split deviates from optimal partition

Discomfort function effectively models pedestrian choices

Individual fluctuations are crucial for accurate predictions

Abstract

Routing choices of walking pedestrians in geometrically complex environments are regulated by the interplay of a multitude of factors such as local crowding, (estimated) time to destination, (perceived) comfort. As individual choices combine, macroscopic traffic flow patterns emerge. Understanding the physical mechanisms yielding macroscopic traffic distributions in environments with complex geometries is an outstanding scientific challenge, with implications in the design and management of crowded pedestrian facilities. In this work, we analyze, by means of extensive real-life pedestrian tracking data, unidirectional flow dynamics in an asymmetric setting, as a prototype for many common complex geometries. Our environment is composed of a main walkway and a slightly longer detour. Our measurements have been collected during a dedicated high-accuracy pedestrian tracking campaign held in Eindhoven (The Netherlands). We show that the dynamics can be quantitatively modeled by introducing a collective discomfort function, and that fluctuations on the behavior of single individuals are crucial to correctly recover the global statistical behavior. Notably, the observed traffic split substantially departs from an optimal, transport-wise, partition, as the global pedestrian throughput is not maximized.