Speed modulated social influence in evacuating pedestrian crowds

Abstract

Evacuation is a complex social phenomenon with individuals tending to exit a confined space as soon as possible. Social factors that influence an individual include collision avoidance and conformity with others with respect to the tendency to exit. While collision avoidance has been heavily focused on by the agent-based models used frequently to simulate evacuation scenarios, these models typically assume that all agents have an equal desire to exit the scene in a given situation. It is more likely that, out of those who are exiting, some are patient while others seek to exit as soon as possible. Here, we experimentally investigate the effect of different proportions of patient (no-rush) versus impatient (rush) individuals in an evacuating crowd of up to 24 people. Our results show that a) average speed changes significantly for individuals who otherwise tended to rush (or not rush) with both type of individuals speeding up in the presence of the other; and b) deviation rate, defined as the amount of turning, changes significantly for the rush individuals in the presence of no-rush individuals. We then seek to replicate this effect with Helbing's social force model with the twin purposes of analyzing how well the model fits experimental data, and explaining the differences in speed in terms of model parameters. We find that we must change the interaction parameters for both rush and no-rush agents depending on the condition that we are modeling in order to fit the model to the experimental data.

Social Force Model parameter testing and optimization using a high stress real-life situation

“…This discrepancy between laboratory and empirical conditions seems to be the reason why the sets of parameters proposed in Refs. [21,23] do not produce evacuation curves in agreement with the empirical data analyzed in this paper.…”

“…In Ref. [23], Lee et al perform an evacuation laboratory experiment varying the proportion of rush/no-rush participants. They used the Wasserstein distance metric to obtain the parameters A and B that best fitted the experimental results.…”

The Effect of An Emergency Evacuation on the Spread of COVID19

“…Specifically, we record an average distance of 1.7 m for A × B ≈ 5 kNm as we vary A from 6 kN to 14 kN and B from 0.4 m to 0.72 m. We selected A 10 kN, and B 0.48 m as the centroid of this region. In the event that experimental data is available, the parameters of the pedestrian dynamics model can be set by minimizing the difference between simulated and experimental trajectories [9], or between distribution of individual speeds [10]. All other parameter values were kept the same as set in the open source code provided as part of Helbing et al [8].…”