Congestion Number Analysis of Cross-Flow Dynamics: Experimental Data and Simulations

Francesco Zanlungo; Zeynep Yucel; Claudio Feliciani; Katsuhiro Nishinari; Takayuki Kanda

doi:10.17815/CD.2024.153

Authors

Francesco Zanlungo Osaka International Professional University, Osaka, Japan https://orcid.org/0000-0002-0992-3202
Zeynep Yucel Okayama University, Okayama, Japan https://orcid.org/0000-0003-3404-4485
Claudio Feliciani The University of Tokyo, Tokyo, Japan https://orcid.org/0000-0003-0718-8707
Katsuhiro Nishinari The University of Tokyo, Tokyo, Japan https://orcid.org/0000-0003-3069-1757
Takayuki Kanda Kyoto University, Kyoto, Japan https://orcid.org/0000-0002-9546-5825

DOI:

https://doi.org/10.17815/CD.2024.153

Keywords:

Pedestrian cross-flows, Model-data comparison, Crowd evacuation metrics

Abstract

We recently proposed the "Congestion Number" (CN) as a metric
to evaluate the state of a pedestrian crowd. Such metric, whose definition is based on the gradient of the rotor of the crowd velocity field, appears to provide additional information with respect to traditional metrics based on pedestrian density and flow.

We also published two works on the dynamics of orthogonally crossing pedestrian flows under different density regimes. In the first manuscript we analysed experimental data by using traditional
observables such as density, velocity and relative position between pedestrians, along with less explored ones such as body orientation. In the second one we proposed a hierarchy of simulation models to reproduce the cross-flow dynamics, and used the aforementioned observables to compare such models.

Based on theoretical considerations and analysis of real world data, we believe the crossing flow setting to be a good arena to test the CN metric, and in this work we perform a CN analysis on the empirical and simulation data. Results show that simulation models, which reproduced almost perfectly the density time dependence of the pedestrian crowd, fail to reproduce the CN one. Actually, models "outperform" the pedestrian crowd when analysed using CN. These preliminary results suggest that the CN metric may provide useful information not only in crowd assessment but also in model evaluation.

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