Predictors of evacuation behavior: dataset on respondents' route choice and web interaction
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články, dataset
Grantová podpora
MUNI/A/1393/2021
Masarykova Univerzita (Masaryk University)
PubMed
39833249
PubMed Central
PMC11747338
DOI
10.1038/s41597-025-04440-y
PII: 10.1038/s41597-025-04440-y
Knihovny.cz E-zdroje
- MeSH
- dospělí MeSH
- internet MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- rozhodování * MeSH
- senioři MeSH
- strojové učení MeSH
- výběrové chování * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. We provide a dataset on human decision-making during evacuations from virtual buildings, captured using experimental methods that controlled specific building layout parameters. An online experiment assigned participants a random subset of tasks featuring T-intersections. Data from 208 respondents, aged 17 to 71, were analyzed, considering education levels and excluding those with significant technical issues. Quantitative data on user interaction and evacuation route choices included decision time, mouse rotation, and the selected corridor, recorded through mouse clicks on invisible areas of interest. Respondents also self-reported their choice confidence on a Likert scale. Additionally, responses to final retrospective evaluation questionnaires were recorded. This dataset offers diverse research opportunities, particularly in emergency evacuation planning, where understanding evacuation choices in simulations can inform real-world strategies. It supports the development of models to predict human behavior in emergencies using machine learning and predictive modeling and is accessible for both academic and commercial use.
Department of Geography Faculty of Science Masaryk University Brno Czech Republic
Department of Psychology Faculty of Arts Masaryk University Brno Czech Republic
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