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Unraveling the causes of the Seoul Halloween crowd-crush disaster

Fig 5

Representation of crowd state prediction and estimation.

(a) The dynamic OD estimation provides an inflow rate for each pedestrian stream, determined through the introduction of a congestion detector. (b) The boundary conditions include the OD information and solid boundaries. (c) The model parameters are derived from an extensive review of empirical studies. (d) Utilizing the input data, a hydrodynamic model is employed that explicitly takes into account the route strategy and aggregated pressure. (e) The dynamic evolution of key crowd states and indicators facilitates the identification of potential crowd risks.

Fig 5

doi: https://doi.org/10.1371/journal.pone.0306764.g005