Many-particle simulation of the evacuation process from a room without visibility

TL;DR

This study combines experiments and simulations to analyze how disoriented individuals evacuate from smoky rooms, revealing non-linear effects like herding and optimal crowd sizes that impact evacuation efficiency and safety planning.

Contribution

It introduces an extended lattice gas model that captures disoriented evacuation behavior and uncovers non-linear effects influencing escape times and crowd dynamics.

Findings

Escape time distribution widens with more people due to jamming.

Adding more exits does not always reduce evacuation time because of herding.

Optimal crowd size minimizes average escape time in smoky conditions.

Abstract

We study the evacuation process from a smoky room by means of experiments and simulations. People in a dark or smoky room are mimicked by ``blind'' students wearing eye masks. The evacuation of the disoriented students from the room is observed by video cameras, and the escape time of each student is measured. We find that the disoriented students exhibit a distinctly different behavior compared with a situation in which people can see and orient themselves. Our experimental results are reproduced by an extended lattice gas model taking into account the empirically observed behavior. Our particular focus is on the mean value and distribution of escape times. For a large number of people in the room, the escape time distribution is wide because of jamming. Surprisingly, adding more exits does not improve the situation in the expected way, since most people use the exit that is discovered first, which may be viewed as ``herding effect'' based on accoustic interactions. Moreover, the average escape time becomes minimal for a certain finite number of people in the dark or smoky room. These non-linear effects have practical implications for emergency evacuation and the planning of safer buildings.