Effect of density control in partially observable asymmetric-exit evacuation under guidance: Strategic suggestion under time delay

Fengqiang Gao, Yuyue Yan, Zhihao Chen, Linxiao Zheng and Huan Ren

Applied Mathematics and Computation, 2022, vol. 418, issue C

Abstract: To enhance the evacuation efficiency in partially observable asymmetric-exit evacuation under guidance, a general framework of the dynamic guiding assistant system is presented to investigate the effect of density control. In this framework, several evacuation assistants are established to observe the partial information of pedestrians’ location and adjust the guiding signals of the dynamic guiding assistant systems. A simple on-off-based density control algorithm is proposed for the evacuation assistants according to the delayed data of the observed information (i.e., pedestrian densities in the observed regions near the corresponding exits). This paper provides strategic suggestions on how to set the observed region and the target density by involving a force-driven cellular automaton model. It is observed that the proposed density control algorithm can control (positively affect) the global distribution of the pedestrians’ locations and suppress arching phenomena in the evacuation process even using the observed partial information under time delays. By imposing a moderate target density, the dynamic guiding assistant system also suppresses the triggers of collisions around the exits and avoids inefficiently separating the pedestrians. To enhance evacuation efficiency, we reveal an interesting fact without loss of generality that we only need to observe the pedestrians’ location from a small region near the exit instead of a large region when the time delay of the observed information is slight enough. Our numerical findings are expected to provide new insights into designing computer-aided guiding strategies in real evacuations.

Keywords: Pedestrian flow; Guided crowd; Computer-aided technology; Evacuation efficiency; Evacuation simulation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:418:y:2022:i:c:s0096300321009218

DOI: 10.1016/j.amc.2021.126838

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