The simulation of wildland-urban interface fire evacuation: The WUI-NITY platform. (April 2021)

• Record Type: Journal Article
• Authors: Wahlqvist, Jonathan; Ronchi, Enrico; Gwynne, Steven M.V.; Kinateder, Max; Rein, Guillermo; Mitchell, Harry; Bénichou, Noureddine; Ma, Chunyun; Kimball, Amanda; Kuligowski, Erica
• Is Part Of: Safety science. Volume 136(2021)
• Publication Date: 2021-04
• Subjects: Wildland-urban interface -- WUI -- Fire -- Evacuation -- Modelling -- Decision making; Industrial accidents -- Periodicals; Accident Prevention -- Periodicals; Safety -- Periodicals; Travail -- Accidents -- Périodiques; 363.11
• DOI: 10.1016/j.ssci.2020.105145
• Languages: English
• ISSNs: 0925-7535

Abstract

Highlights: The WUI-NITY platform for the simulation of WUI fire evacuation is presented. WUI-NITY models fire, pedestrian and traffic in a coupled manner. WUI-NITY enhances situational awareness in evacuation scenarios. 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.