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Traffic Flow Data Collection Methods During Wildfire Evacuation

Dugstad, Ann Kristin LU ; Berthiaume, Maxine ; Ronchi, Enrico LU orcid ; Bénichou, Noureddine ; Geoerg, Paul ; Gwynne, Steve LU ; Xie, Hui ; Kubose-Peutz, Kamryn ; Kimball, Amanda and Kinateder, Max (2026) In Fire and Materials
Abstract

With climate change and urbanisation increasing wildfire risk in the wildland–urban interface (WUI), enhancing community evacuation preparedness is crucial. This study evaluates different data collection methods for measuring traffic flows during a community wildfire evacuation drill in Roxborough Park, Colorado, in June 2024. A multi-method strategy was applied, including drone footage, human observers (manual and app-assisted), automated traffic counters, questionnaires, and postcards. Methods were assessed based on cost, ease of use, data quality, privacy, and ethical considerations. Results highlight that drone footage effectively captured large-scale traffic flow but required a large number of resources for preparation and... (More)

With climate change and urbanisation increasing wildfire risk in the wildland–urban interface (WUI), enhancing community evacuation preparedness is crucial. This study evaluates different data collection methods for measuring traffic flows during a community wildfire evacuation drill in Roxborough Park, Colorado, in June 2024. A multi-method strategy was applied, including drone footage, human observers (manual and app-assisted), automated traffic counters, questionnaires, and postcards. Methods were assessed based on cost, ease of use, data quality, privacy, and ethical considerations. Results highlight that drone footage effectively captured large-scale traffic flow but required a large number of resources for preparation and post-processing. Human observers provided detailed insights but might be prone to errors in high-traffic areas. Self-reported data (questionnaires, postcards) offered valuable behavioural insights but might be affected by response bias. Automated traffic counters provided continuous data but could not differentiate between drill-specific and background traffic. This study provides practical guidance on selecting behavioural data collection methods for wildfire evacuation research, ultimately contributing to improved emergency planning and community resilience.

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author
; ; ; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
in press
subject
keywords
evacuation, human behaviour in fire, traffic flow, wildfire, wildland–urban interface, WUI
in
Fire and Materials
publisher
John Wiley & Sons Inc.
external identifiers
  • scopus:105039061372
ISSN
0308-0501
DOI
10.1002/fam.70077
language
English
LU publication?
yes
id
b79cab5a-5c3f-49cc-be16-fa109237d596
date added to LUP
2026-07-09 13:04:07
date last changed
2026-07-09 13:04:25
@article{b79cab5a-5c3f-49cc-be16-fa109237d596,
  abstract     = {{<p>With climate change and urbanisation increasing wildfire risk in the wildland–urban interface (WUI), enhancing community evacuation preparedness is crucial. This study evaluates different data collection methods for measuring traffic flows during a community wildfire evacuation drill in Roxborough Park, Colorado, in June 2024. A multi-method strategy was applied, including drone footage, human observers (manual and app-assisted), automated traffic counters, questionnaires, and postcards. Methods were assessed based on cost, ease of use, data quality, privacy, and ethical considerations. Results highlight that drone footage effectively captured large-scale traffic flow but required a large number of resources for preparation and post-processing. Human observers provided detailed insights but might be prone to errors in high-traffic areas. Self-reported data (questionnaires, postcards) offered valuable behavioural insights but might be affected by response bias. Automated traffic counters provided continuous data but could not differentiate between drill-specific and background traffic. This study provides practical guidance on selecting behavioural data collection methods for wildfire evacuation research, ultimately contributing to improved emergency planning and community resilience.</p>}},
  author       = {{Dugstad, Ann Kristin and Berthiaume, Maxine and Ronchi, Enrico and Bénichou, Noureddine and Geoerg, Paul and Gwynne, Steve and Xie, Hui and Kubose-Peutz, Kamryn and Kimball, Amanda and Kinateder, Max}},
  issn         = {{0308-0501}},
  keywords     = {{evacuation; human behaviour in fire; traffic flow; wildfire; wildland–urban interface; WUI}},
  language     = {{eng}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Fire and Materials}},
  title        = {{Traffic Flow Data Collection Methods During Wildfire Evacuation}},
  url          = {{http://dx.doi.org/10.1002/fam.70077}},
  doi          = {{10.1002/fam.70077}},
  year         = {{2026}},
}