Artikel

Safety evaluation of evacuation routes in Central Tokyo assuming a large-scale evacuation in case of earthquake disasters

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.

Language
Englisch

Bibliographic citation
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 10 ; Year: 2017 ; Issue: 3 ; Pages: 1-21 ; Basel: MDPI

Classification
Management
Subject
large-scale evacuation
evacuation route
safety evaluation
earthquake disaster
Ant Colony Optimization (ACO)
Geographic Information Systems (GIS)

Event
Geistige Schöpfung
(who)
Yamamoto, Kayoko
Li, Ximing
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2017

DOI
doi:10.3390/jrfm10030014
Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Yamamoto, Kayoko
  • Li, Ximing
  • MDPI

Time of origin

  • 2017

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