Back to Search
Start Over
Development of human-in-the-loop experiment system to extract evacuation behavioral features: A case of evacuees in nuclear emergencies
- Source :
- Nuclear Engineering and Technology, Vol 55, Iss 6, Pp 2246-2255 (2023)
- Publication Year :
- 2023
- Publisher :
- Elsevier, 2023.
-
Abstract
- Evacuation time estimation (ETE) is crucial for the effective implementation of resident protection measures as well as planning, owing to its applicability to nuclear emergencies. However, as confirmed in the Fukushima case, the ETE performed by nuclear operators does not reflect behavioral features, exposing thus, gaps that are likely to appear in real-world situations. Existing research methods including surveys and interviews have limitations in extracting highly feasible behavioral features. To overcome these limitations, we propose a VR-based immersive experiment system. The VR system realistically simulates nuclear emergencies by structuring existing disasters and human decision processes in response to the disasters. Evacuation behavioral features were quantitatively extracted through the proposed experiment system, and this system was systematically verified by statistical analysis and a comparative study of experimental results based on previous research. In addition, as part of future work, an application method that can simulate multi-level evacuation dynamics was proposed. The proposed experiment system is significant in presenting an innovative methodology for quantitatively extracting human behavioral features that have not been comprehensively studied in evacuation. It is expected that more realistic evacuation behavioral features can be collected through additional experiments and studies of various evacuation factors in the future.
Details
- Language :
- English
- ISSN :
- 17385733
- Volume :
- 55
- Issue :
- 6
- Database :
- Directory of Open Access Journals
- Journal :
- Nuclear Engineering and Technology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0a8396cc87a142d4ae53b073cdf022c4
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.net.2023.02.032