Variable guiding strategies in multi-exits evacuation: Pursuing balanced pedestrian densities

Huan Ren, Yuyue Yan and Fengqiang Gao

Applied Mathematics and Computation, 2021, vol. 397, issue C

Abstract: Evacuation assistants and their guiding strategies play an important role in the multi-exits pedestrian evacuation. To investigate the effects of guiding strategies on evacuation efficiency, we propose a force-driven cellular automaton model with adjustable guiding attractions imposed by the evacuation assistants located in the exits. In this model, each of the evacuation assistants tries to attract the pedestrians in the evacuation space towards its own exit by sending a quantifiable guiding signal, which may be adjusted according to the values of pedestrian density near the exit. The effects of guiding strategies pursuing balanced pedestrian densities are studied. It is observed that the unbalanced pedestrian distribution is mainly yielded by a snowballing effect generated from the mutual attractions among the pedestrians, and can be suppressed by controlling the pedestrian densities around the exits. We also reveal an interesting fact that given a moderate target density value, the density control for the partial regions (near the exits) could yield a global effect for balancing the pedestrians in the rest of the regions and hence improve the evacuation efficiency. Our findings may contribute to give new insight into designing effective guiding strategies in the realistic evacuation process.

Keywords: Force-driven cellular automaton model; Pedestrian flow; Guided crowd; Evacuation efficiency; Crowd control (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:397:y:2021:i:c:s0096300321000138

DOI: 10.1016/j.amc.2021.125965

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