- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- 【Updated on June 30, 2025】Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
-
- Yoshitsugu Nagi
- Tokyo Metropolitan Industrial Technology Research Institute
-
- Abe Shinya
- Tokyo Metropolitan Industrial Technology Research Institute
-
- Yamamoto Kayoko
- The University of Electro-Communications
Search this article
Description
<p>Achieving safe evacuation is the main goal of selecting an evacuation route. General path-finding methods determine a single shortest route to one end point; however, this is insufficient for selecting evacuation routes. Central Tokyo has a dense population with many tourists, and there are many areas with high disaster risk, such as densely populated wooden houses. As a result, it is important to prepare multiple evacuation sites and routes in case the optimal ones become unavailable. At present, the safety of evacuation routes is determined empirically; however, it should also be evaluated by quantitatively comparing multiple evacuation route candidates. In this paper, we propose a method for simultaneously deriving multiple evacuation route candidates using the Physarum solver. This method also quantitatively considers disaster risk. To evaluate the safety of the evacuation routes derived by this method, we define an index called the evacuation success rate. By developing a method for obtaining multiple evacuation routes considering disaster risk and by providing an index for quantitatively evaluating the safety of the obtained evacuation routes, safe and rapid evacuation can be achieved during disasters.</p>
Journal
-
- Journal of Information Processing
-
Journal of Information Processing 28 (0), 1065-1072, 2020
Information Processing Society of Japan
- Tweet
Details 詳細情報について
-
- CRID
- 1390849931313296128
-
- NII Article ID
- 170000184161
- 130007956182
-
- NII Book ID
- AN00116647
-
- ISSN
- 18827764
- 18826652
-
- Text Lang
- en
-
- Article Type
- journal article
-
- Data Source
-
- JaLC
- IRDB
- Crossref
- CiNii Articles
- KAKEN
- OpenAIRE
-
- Abstract License Flag
- Disallowed