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Large crowd modelling: an analysis of the Duisburg Love Parade disaster

机译:大型人群建模:杜伊斯堡爱情游行灾难分析

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Given the amount of data publically available relating to the incident at the Duisburg Love Parade of 2010, this event is a valuable case study for the development and management of large-scale crowd circulation and emergency incidents. Here, we study the crowd dynamics associated with a large crowd event similar to that of the Love Parade in Duisburg. The paper discusses the analysis of observations of the incident and explores the application of an evacuation model to investigate similar crowd scenarios. The data-set produced from this analysis was used to configure the buildingEXODUS model to approximate the original incident to verify whether buildingEXODUS can reliably represent agent actions, the conditions that develop and the impact of these developments upon performance. The model is then used to identify potential alternative crowd management and ingress/egress strategies to prevent the crowd crush incident from occurring. Traditionally, fine mesh evacuation models, such as buildingEXODUS, are not used to investigate high-density crowd conditions, because the underlying discretisation of space limits the maximum density that can be achieved within the models. In this paper, a novel approach is used to combine the data of pedestrian flow and space utilisation to indicate the onset of potentially dangerous population densities using a fine node model. The analysis demonstrates that the model can capture the key elements of such a large-scale incident and identify important causal factors. The work demonstrates that the model is broadly able to capture key crowd features if representative assumptions are implemented. Copyright (c) 2013 John Wiley & Sons, Ltd.
机译:考虑到2010年杜伊斯堡爱情大游行上与该事件有关的公开数据量很大,该事件对于大规模人群传播和紧急事件的开发和管理是一个有价值的案例研究。在这里,我们研究与杜伊斯堡爱情大游行相似的大型人群事件的人群动态。本文讨论了对事件观察的分析,并探讨了疏散模型在调查相似人群场景中的应用。从该分析产生的数据集用于配置buildingEXODUS模型以近似原始事件,以验证buildingEXODUS是否可以可靠地表示代理行为,发展的条件以及这些发展对性能的影响。然后,该模型用于识别潜在的替代人群管理和入口/出口策略,以防止发生人群挤压事件。传统上,精细的网格疏散模型(例如buildingEXODUS)不用于研究高密度人群条件,因为潜在的空间离散化限制了模型内可实现的最大密度。在本文中,一种新颖的方法被用来结合行人流和空间利用的数据,以使用精细节点模型指示潜在危险的人口密度的开始。分析表明,该模型可以捕获此类大规模事件的关键要素并确定重要的因果关系。这项工作表明,如果实施了代表性的假设,该模型就能广泛地捕获关键人群特征。版权所有(c)2013 John Wiley&Sons,Ltd.

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