Conflict Avoidance in Pedestrian Merging in Controlled Experiments by Variance Indicator

TL;DR

This study introduces variance-based indicators to distinguish geometric and interaction effects in pedestrian merging flows, revealing a critical transition near 90 degrees and improving understanding of pedestrian congestion at corridor intersections.

Contribution

The paper presents a novel use of Voronoi-based speed and velocity variance measures to differentiate between geometric and interaction-induced fluctuations in pedestrian merging flows.

Findings

Variance indicators effectively identify interaction-driven instability.

A critical transition near 90 degrees turning angle was observed.

Variance measures outperform traditional density and speed metrics.

Abstract

Pedestrian congestion at corridor intersections often originates from localized fluctuations in motion rather than from a macroscopic collapse of flow. Understanding pedestrian instability at corridor intersections remains challenging because existing studies mainly rely on density, average speed, or flow-based measures and limited datasets, making it difficult to separate geometric turning effects from interaction induced fluctuations in merging flows. In particular, the mechanism underlying the turning angle dependence in T junctions has not been resolved. Here, we analyze more than 300 controlled experiments conducted in L corridors with turning only and T corridors with turning and merging. Using Voronoi-based speed variance $V_s$ and velocity variance $V_v$, we systematically compare geometric and interaction effects. $V_s$ effectively captures interaction driven instability, while $V_v$ reflects directional adjustments due to geometry. The comparison reveals distinct fluctuation mechanisms and identifies a critical transition near $90{\deg}$, demonstrating the advantage of variance-based indicators for diagnosing pedestrian dynamics.