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Safety Evaluation of Evacuation Routes in Central Tokyo Assuming a Large-Scale Evacuation in Case of Earthquake Disasters

机译:假设发生地震时进行大规模避难的东京市中心避难路线的安全性评估

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The present study aims to conduct a quantitative evaluation of evacuation route safety using the Ant Colony Optimization (ACO) algorithm for risk management in central Tokyo. Firstly, the similarity in safety was focused on while taking into consideration road blockage probability. Then, by classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of Geographic Information Systems (GIS), and their safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites for cases when the possibility of large-scale evacuation after an earthquake disaster is high is made possible. As the evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas, regardless of whether the information is from the past or future. Therefore, in addition to spatial reproducibility, the evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, the selected highly safe evacuation routes have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.
机译:本研究旨在使用蚁群优化(ACO)算法对东京市中心的风险管理进行疏散路线安全性的定量评估。首先,在考虑道路阻塞概率的同时,重点关注安全性的相似性。然后,通过分层聚类分析对道路进行分类,使用ACO模拟估算疏散路线的拥堵率。根据这些结果,通过地理信息系统(GIS)在数字地图上可视化提取的多个疏散路线,并评估其安全性。此外,对于在地震灾难后大规模撤离的可能性很高的情况,可以选择撤离地点之间的安全撤离路线。由于评估方法是基于公共信息的,因此,通过获取与本研究相同的地理信息,无论信息来自过去还是未来,它在其他领域都有效。因此,除了空间可再现性之外,评估方法还具有较高的时间可再现性。由于基于量化数据对避难路线进行了安全性评估,因此已对选定的高度安全的避难路线进行了定量评估,因此可以作为选择避难路线时的有效指标。

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