基于不适程度的有效监管出口模型和问卷调查

IF 0.7 Q4 GEOSCIENCES, MULTIDISCIPLINARY Journal of Disaster Research Pub Date : 2024-04-01 DOI:10.20965/jdr.2024.p0279
Riku Miyagawa, D. Yanagisawa, Xiaolu Jia, Yasushi Shoji, Tetsuya Aikoh, K. Nishinari
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引用次数: 0

摘要

在大型活动结束后,通常会进行有序疏散,以避免活动场所周围的车站出现极端拥堵。在有序疏散过程中,人们被分成若干组,按顺序疏散。通过控制小组数量和每组之间的出口时间间隔,管理人员可以缓解车站的拥堵状况。本研究建立了一个数学模型,以确定有效的调控出口。不适程度(LOD)被用来评估调控出口的性能,而不是总出口时间。LOD 是出口密度和出口时间的函数乘积,代表了出口过程中累积的不适感。为确定 LOD 函数参数进行了问卷调查。在假定条件下,校准模型的结果表明,可以通过将人员分为两组或三组来进行有效的规范出口,这在现实世界的管理方面是可以推定的。除了有效组数的主要结果外,通过比较两类 LOD 函数的结果,也证实了模型的稳健性。换句话说,有效组数与 LOD 函数的详细形式并无很大关系。
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Modeling and Questionnaire Survey for Effective Regulated Egress Based on Level of Discomfort
Regulated egress is often conducted after large events to avoid extreme congestion at stations around event venues. In regulated egress, people are divided into several groups and egress in order. By controlling the number of groups and the time interval between each group’s egress, managers can mitigate the congestion at the stations. In this study, a mathematical model was developed to identify the effective regulated egress. level of discomfort (LOD) was used to evaluate the performance of the regulated egress instead of the total egress time. LOD is the product of the function of density and duration of egress and represents the accumulated discomfort through the egress. A questionnaire survey was conducted to determine the LOD function parameters. Under the assumed conditions, the results of the calibrated model indicated that effective regulated egress could be conducted by dividing the people into two or three groups, which is presumable in terms of management in the real world. In addition to the main result for the effective number of groups, the robustness of the model was confirmed by comparing the results of the two types of LOD functions. In other words, the effective number of groups does not strongly depend on the detailed form of the LOD functions.
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来源期刊
Journal of Disaster Research
Journal of Disaster Research GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
1.60
自引率
37.50%
发文量
113
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