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WUI-NITY 4 : An Industry-Ready WUI Fire Evacuation Model

Ronchi, Enrico LU orcid ; Wahlqvist, Jonathan LU ; Rohaert, Tuur LU orcid ; Kuligowski, Erica ; Wu, Junfeng ; Zhou, Xiangmin ; Singh, Dhirendra ; Rein, Guillermo ; Mitchell, Harry and Kalogeropoulos, Nikolaos , et al. (2024)
Abstract
In recent years, WUI fire evacuation models have started to be developed. Several now exist, although they are primarily research tools unable to be applied in practice or commercially available tools with limited functionality. For this step – moving from research to practice – such models need to build their credibility through data for their development, testing and application. The WUI-NITY tool has been developed over several previously NIST-funded projects. This project aims at providing a set of useful methods for the development and validation of wildfire evacuation models. This includes social media data mining techniques for the investigation of evacuation behavior and the use of virtual reality technology to explore driving... (More)
In recent years, WUI fire evacuation models have started to be developed. Several now exist, although they are primarily research tools unable to be applied in practice or commercially available tools with limited functionality. For this step – moving from research to practice – such models need to build their credibility through data for their development, testing and application. The WUI-NITY tool has been developed over several previously NIST-funded projects. This project aims at providing a set of useful methods for the development and validation of wildfire evacuation models. This includes social media data mining techniques for the investigation of evacuation behavior and the use of virtual reality technology to explore driving behavior during wildfire scenarios. Those two methods are exemplified through a set of data collection and analysis efforts for which results are made freely available to any interested party. This report also presents the latest enhancements of the WUI-NITY tool and its associated trigger buffer tool K-Peril. This includes the implementation of a microscopic traffic model (SUMO) and the definition of stochastic trigger boundaries. Finally, this report presents information useful for a model user to configure a WUI-NITY simulation through a dedicated user guide. All these activities contribute to the development of a tool that can be used for free by any interested party to investigate wildfire evacuation behavior. (Less)
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organization
publishing date
type
Book/Report
publication status
published
subject
keywords
wildfire, evacuation, fire safety, evacuation simulation, LLM, bushfire, social media, data mining, virtual reality
pages
223 pages
publisher
Fire Protection Research Foundation
language
English
LU publication?
yes
id
17840ec1-233f-488d-b292-e8cf420552c5
date added to LUP
2025-08-07 15:03:24
date last changed
2025-08-13 10:34:46
@techreport{17840ec1-233f-488d-b292-e8cf420552c5,
  abstract     = {{In recent years, WUI fire evacuation models have started to be developed. Several now exist, although they are primarily research tools unable to be applied in practice or commercially available tools with limited functionality. For this step – moving from research to practice – such models need to build their credibility through data for their development, testing and application. The WUI-NITY tool has been developed over several previously NIST-funded projects. This project aims at providing a set of useful methods for the development and validation of wildfire evacuation models. This includes social media data mining techniques for the investigation of evacuation behavior and the use of virtual reality technology to explore driving behavior during wildfire scenarios. Those two methods are exemplified through a set of data  collection and analysis efforts for which results are made freely available to any interested party. This report also presents the latest enhancements of the WUI-NITY tool and its associated trigger buffer tool K-Peril. This includes the implementation of a microscopic traffic model (SUMO) and the definition of stochastic trigger boundaries. Finally, this report presents information useful for a model user to configure a WUI-NITY simulation through a dedicated user guide. All these activities contribute to the development of a tool that can be used for free by any interested party to investigate wildfire evacuation behavior.}},
  author       = {{Ronchi, Enrico and Wahlqvist, Jonathan and Rohaert, Tuur and Kuligowski, Erica and Wu, Junfeng and Zhou, Xiangmin and Singh, Dhirendra and Rein, Guillermo and Mitchell, Harry and Kalogeropoulos, Nikolaos and Gwynne, Steve and Xie, Hui and Thompson, Peter and Kinateder, Max and Berthiaume, Maxine and Bénichou, Noureddine and Kimball, Amanda}},
  institution  = {{Fire Protection Research Foundation}},
  keywords     = {{wildfire; evacuation; fire safety; evacuation simulation; LLM; bushfire; social media; data mining; virtual reality}},
  language     = {{eng}},
  title        = {{WUI-NITY 4 : An Industry-Ready WUI Fire Evacuation Model}},
  url          = {{https://lup.lub.lu.se/search/files/224899975/WUI-NITY4.pdf}},
  year         = {{2024}},
}