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WUI-NITY 3 : Multi-method traffic movement data collection for WUI fire evacuation modelling

Ronchi, Enrico LU orcid ; Wahlqvist, Jonathan LU ; Rohaert, Arthur LU orcid ; Kuligowski, Erica ; Janfeshanaraghi, Nima ; Rein, Guillermo ; Mitchell, Harry ; Kalogeropoulos, Nikolaos ; Gwynne, Steve LU and Xie, Hui , et al. (2023)
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. For this step – moving from research to practice – such models need to build their credibility through testing and application. The WUI-NITY tool has been developed over several previously NIST-funded projects. Once this model is suitably tested and deemed usable, it can be adopted to test different application scenarios as part of engineering practice – beyond simply research applications. The testing process is currently underway; however, it is constrained by the current lack of suitable, available data. In particular, there is a clear need for more data regarding... (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. For this step – moving from research to practice – such models need to build their credibility through testing and application. The WUI-NITY tool has been developed over several previously NIST-funded projects. Once this model is suitably tested and deemed usable, it can be adopted to test different application scenarios as part of engineering practice – beyond simply research applications. The testing process is currently underway; however, it is constrained by the current lack of suitable, available data. In particular, there is a clear need for more data regarding traffic movement during emergency response. Data concerning traffic evacuation is rare enough; however, data sets that can be applied at the required degree of granularity for evacuation models such as WUI-NITY are scarce in the scientific literature. In this project, several activities have been carried out to enhance data availability for WUI fire evacuation models and improve the WUI-NITY capabilities. This includes:
• The development of methodology for traffic evacuation data extraction.
• The analysis of the Caltrans Performance Measurement System (PeMS) to demonstrate the applicability of the methodology for data extraction.
• The public release of two data sets from actual fires, the 2020 Glass fire and the 2020 Silverado Fire. These data sets are published in open access for any interested party (not only for WUI-NITY, but any model developer/user/researcher).
• The exploratory use of Virtual Reality technology to study traffic evacuation movement variables which we cannot systematically investigate from existing databases (e.g., interaction with information provided by variable message signs). The goal is to use this
approach to complement other modes of data collection given the implausibility of performing traditional experiments exploring key unknowns.
• An improved integration of a trigger buffer model (k-PERIL) into WUI-NITY which includes an initial integration of stochastic trigger models.
• The enhancement of WUI-NITY tool. Data obtained were used to improve the WUI-NITY representation of the traffic modelling layer.
• The graphical user interface (GUI) of the model was also improved to ensure that WUI-NITY can be used by a wider range of users and to facilitate its application through clarifying its workflow. (Less)
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organization
publishing date
type
Book/Report
publication status
published
subject
pages
114 pages
publisher
Fire Protection Research Foundation
language
English
LU publication?
yes
id
596ec536-bd2c-48f5-8ee9-986d7ccdd987
date added to LUP
2025-09-05 08:17:24
date last changed
2025-09-11 11:51:02
@techreport{596ec536-bd2c-48f5-8ee9-986d7ccdd987,
  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. For this step – moving from research to practice – such models need to build their credibility through testing and application. The WUI-NITY tool has been developed over several previously NIST-funded projects. Once this model is suitably tested and deemed usable, it can be adopted to test different application scenarios as part of engineering practice – beyond simply research applications. The testing process is currently underway; however, it is constrained by the current lack of suitable, available data. In particular, there is a clear need for more data regarding traffic movement during emergency response. Data concerning traffic evacuation is rare enough; however, data sets that can be applied at the required degree of granularity for evacuation models such as WUI-NITY are scarce in the scientific literature. In this project, several activities have been carried out to enhance data availability for WUI fire evacuation models and improve the WUI-NITY capabilities. This includes:<br/>• The development of methodology for traffic evacuation data extraction.<br/>• The analysis of the Caltrans Performance Measurement System (PeMS) to demonstrate the applicability of the methodology for data extraction.<br/>• The public release of two data sets from actual fires, the 2020 Glass fire and the 2020 Silverado Fire. These data sets are published in open access for any interested party (not only for WUI-NITY, but any model developer/user/researcher).<br/>• The exploratory use of Virtual Reality technology to study traffic evacuation movement variables which we cannot systematically investigate from existing databases (e.g., interaction with information provided by variable message signs). The goal is to use this<br/>approach to complement other modes of data collection given the implausibility of performing traditional experiments exploring key unknowns.<br/>• An improved integration of a trigger buffer model (k-PERIL) into WUI-NITY which includes an initial integration of stochastic trigger models.<br/>• The enhancement of WUI-NITY tool. Data obtained were used to improve the WUI-NITY representation of the traffic modelling layer.<br/>• The graphical user interface (GUI) of the model was also improved to ensure that WUI-NITY can be used by a wider range of users and to facilitate its application through clarifying its workflow.}},
  author       = {{Ronchi, Enrico and Wahlqvist, Jonathan and Rohaert, Arthur and Kuligowski, Erica and Janfeshanaraghi, Nima and Rein, Guillermo and Mitchell, Harry and Kalogeropoulos, Nikolaos and Gwynne, Steve and Xie, Hui and Thompson, Peter and Kinateder, Max and Mozaffari Maaref, Hamed and Berthiaume, Maxine and Daoust-Seguin, Jonathan and Bénichou, Noureddine and Kimball, Amanda}},
  institution  = {{Fire Protection Research Foundation}},
  language     = {{eng}},
  title        = {{WUI-NITY 3 : Multi-method traffic movement data collection for WUI fire evacuation modelling}},
  url          = {{https://lup.lub.lu.se/search/files/227071160/WUI-NITY3.pdf}},
  year         = {{2023}},
}