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理解出口处的人类排队行为:一项实证研究。

Understanding human queuing behaviour at exits: an empirical study.

作者信息

Wagoum A U Kemloh, Tordeux A, Liao W

机构信息

Jülich Supercomputing Centre , Forschungszentrum Jülich , Jülich, Germany.

Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany; Computer Simulation for Fire Safety and Pedestrian Traffic, University of Wuppertal, Wuppertal, Germany.

出版信息

R Soc Open Sci. 2017 Jan 25;4(1):160896. doi: 10.1098/rsos.160896. eCollection 2017 Jan.

Abstract

The choice of the exit to egress from a facility plays a fundamental role in pedestrian modelling and simulation. Yet, empirical evidence for backing up simulation is scarce. In this contribution, we present three new groups of experiments that we conducted in different geometries. We varied parameters such as the width of the doors, the initial location and number of pedestrians which in turn affected their perception of the environment. We extracted and analysed relevant indicators such as distance to the exits and density levels. The results put in evidence the fact that pedestrians use time-dependent information to optimize their exit choice, and that, in congested states, a load balancing over the exits occurs. We propose a minimal modelling approach that covers those situations, especially the cases where the geometry does not show a symmetrical configuration. Most of the models try to achieve the load balancing by simulating the system and solving optimization problems. We show statistically and by simulation that a linear model based on the distance to the exits and the density levels around the exit can be an efficient dynamical alternative.

摘要

设施出口的选择在行人建模与模拟中起着至关重要的作用。然而,用于支持模拟的实证证据却很匮乏。在本论文中,我们展示了在不同几何形状下进行的三组新实验。我们改变了诸如门的宽度、行人的初始位置和数量等参数,这些参数进而影响了他们对环境的感知。我们提取并分析了诸如到出口的距离和密度水平等相关指标。结果表明,行人会利用随时间变化的信息来优化他们的出口选择,并且在拥堵状态下,出口会出现负载均衡。我们提出了一种最小化建模方法来涵盖这些情况,特别是几何形状不对称的情况。大多数模型试图通过模拟系统和解决优化问题来实现负载均衡。我们通过统计和模拟表明,基于到出口的距离和出口周围密度水平的线性模型可以是一种有效的动态替代方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2bb/5319354/103f8c214b1b/rsos160896-g1.jpg

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