The simulation of wildland-urban interface fire evacuation: The WUI-NITY platform
File(s)1-s2.0-S0925753520305415-main.pdf (6.57 MB)
Published version
OA Location
Author(s)
Type
Journal Article
Abstract
Wildfires are a significant safety risk to populations adjacent to wildland areas, known as the wildland-urban interface (WUI). This paper introduces a modelling platform called WUI-NITY. The platform is built on the Unity3D game engine and simulates and visualises human behaviour and wildfire spread during an evacuation of WUI communities. The purpose of this platform is to enhance the situational awareness of responders and residents during evacuation scenarios by providing information on the dynamic evolution of the emergency. WUI-NITY represents current and predicted conditions by coupling the three key modelling layers of wildfire evacuation, namely the fire, pedestrian, and traffic movement. This allows predictions of evacuation behaviour over time. The current version of WUI-NITY demonstrates the feasibility and advantages of coupling the modelling layers. Its wildfire modelling layer is based on FARSITE, the pedestrian layer implements a dedicated pedestrian response and movement model, and the traffic layer includes a traffic evacuation model based on the Lighthill-Whitham-Richards model. The platform also includes a sub-model called PERIL that designs the spatial location of trigger buffers. The main contribution of this work is in the development of a modular and model-agnostic (i.e., not linked to a specific model) platform with consistent levels of granularity (allowing a comparable modelling resolution in the representation of each layer) in all three modelling layers. WUI-NITY is a powerful tool to protect against wildfires; it can enable education and training of communities, forensic studies of past evacuations and dynamic vulnerability assessment of ongoing emergencies.
Date Issued
2021-04
Date Acceptance
2020-12-21
Citation
Safety Science, 2021, 136, pp.1-12
ISSN
0925-7535
Publisher
Elsevier BV
Start Page
1
End Page
12
Journal / Book Title
Safety Science
Volume
136
Copyright Statement
© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Sponsor
National Institute of Standards & Technology(NIST)
Identifier
https://www.sciencedirect.com/science/article/pii/S0925753520305415?via%3Dihub
Grant Number
n/a
Subjects
Human Factors
09 Engineering
11 Medical and Health Sciences
17 Psychology and Cognitive Sciences
Publication Status
Published
Article Number
105145
Date Publish Online
2021-01-26