Influence of Gender Composition in Pedestrian Single-File Experiments

TL;DR

This study investigates how gender composition affects pedestrian movement in single-file experiments, finding gender influence only at low densities and no effect at high densities, with human factors not significantly impacting velocity.

Contribution

It provides new insights into gender effects in pedestrian flow, showing gender influence is limited to specific density ranges and that human factors have minimal impact at high densities.

Findings

Gender effect observed only at low densities

No significant gender influence on inter-person distances at high densities

Additional human factors do not improve velocity prediction models

Abstract

Various studies address the question of what factors are relevant to the course of the fundamental diagram in single-file experiments. Some indicate that there are differences due to group composition when gender is taken into account. For this reason, further single-file experiments with homogeneous and heterogeneous group compositions were conducted. A Tukey HSD test was performed to investigate whether there are differences between the mean of velocity in different density ranges. A comparison of different group compositions shows that the effect of gender can only be seen, if at all, in a small density interval. Regression analyses were also conducted to determine whether, at high densities, the distance between individuals depends on the gender of the neighboring pedestrians and to establish what human factors have an effect on the velocity. An analysis of the distances between individuals at high densities indicates that there is no effect of the gender of the neighboring pedestrians. Taking into account additional human factors in a regression analysis does not improve the model.