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VARIANCE ANALYSIS OF MARITIME PASSENGER CLUSTERS TRAVEL SPEEDS WITH REGARDS TO THE HEAD'S WALKING SPEED AND HEAD COUNTS

机译:对头部步行速度和头部统计的海上乘客集群的方差分析

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The purpose of this study is to determine the movement speed of maritime passenger clusters during evacuations, based on an experimental Korean maritime data set. We primarily focus on how much two factors affect overall group travel time: the walking speed of the head of a small passenger group and the number of people in the group. We use an egress model (maritimeEXODUS) to predict maritime passengers' egress behaviour, with regard to aspects such as travel time, density, flow rate, crowd congestion and clustering pattern. Many researchers have studied and analysed occupants' physical characteristics using full-scale experimental data sets, in some cases addressing occupant groups or crowd behaviours. For example, Zeitz has analysed crowd behaviours in mass gatherings, while Klüpfel studied crowd movement by engaging in egress simulation modelling. Other studies have also dealt with psychological aspects. Crowd movement is usually not based on the individual characteristics of crowd members, such as their free walking speed, gender, or personality. Therefore, it is not easy to study factors that affect group or crowd movement behaviours, and it is impossible to do so in uncontrolled observation studies. The analysis of detailed content is also difficult. As such, differences between factors are generally quantified and then used to develop crowd models for controlled experiments. This can help engineers to develop egress simulation models. In general, it is difficult to observe the members of a crowd and their movements. In evacuation situations, more than ten people might move toward the same destination together along a corridor. The number of members of a crowd is closely related to the crowd's velocity. For this study, we conducted an experiment assuming an egress situation on a vessel. The crew of the vessel acted as evacuation guides for 40 passengers, with one person leading an evacuation group as its head. In order to understand the relationship between the walking speed of the head of the group and the rest of its members, we invited 40 passengers to board a ship. We first analysed the head of the group's impact on its travel speed, and then the relationship between individual free walking speeds and passenger group travel speeds. Under normal-controlled conditions, a number of controlled factors were selected in order to measure their influence on the results. The experimental venue was a U-shaped corridor that was 63 metres long and 1.2 metres width. The participants' free walking speeds were measured under experimental conditions. Before the experiment, cameras were installed on the ceiling to record all behaviours. The experiment consisted of 9 sub-experiments, involving different numbers of passengers in groups. For comparison, the walking speeds of the 40 participants were measured in all cases, and individual free walking and group movement speeds were also compared.
机译:本研究的目的是根据实验韩国海事数据集确定疏散期间的海上乘客群的运动速度。我们主要关注两个因素影响整体集团旅行时间:小型客运集团负责人的步行速度以及集团中的人数。我们使用出口模型(MaritimeeXodus)来预测海上乘客的出口行为,关于旅行时间,密度,流速,人群拥塞和聚类模式等方面。在解决占用团体或人群行为的某些情况下,许多研究人员已经使用全规模的实验数据集进行了研究和分析了乘客的物理特征。例如,Zeitz分析了群众聚会中的人群行为,而Klüpfel通过从事Egring仿真建模研究人群运动。其他研究也处理了心理方面。人群运动通常不是基于人群成员的个性特征,例如他们的自由行速,性别或个性。因此,它是不容易的研究影响或一群运动行为的因素,而这是不可能的不受控制的观察研究这样做。详细内容的分析也很困难。因此,通常量化因子之间的差异,然后用于开发用于受控实验的人群模型。这可以帮助工程师开发出口仿真模型。一般来说,很难观察人群的成员及其运动。在疏散情况下,十多个人可能沿着走廊一起朝着同一个目的地移动。人群成员人数与人群的速度密切相关。对于这项研究,我们在船上进行了出口情况进行了实验。该船的船员担任40名乘客的疏散指南,一个人带领疏散组作为头部。为了了解集团负责人和其余成员的行走速度之间的关系,我们邀请了40名乘客登船。我们首先分析了本集团对其旅行速度的影响,然后是个人自由步行速度与乘客群旅行速度之间的关系。在正常控制的条件下,选择了许多受控因素以测量它们对结果的影响。实验场地是U形走廊,长63米,宽1.2米。参与者的自由步行速度在实验条件下测量。在实验之前,在天花板上安装相机以记录所有行为。实验包括9个子实验,包括不同数量的乘客。为了比较,在所有情况下测量了40名参与者的步行速度,并且还比较了单独的自由行走和群体运动速度。

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