Evacuation decision-making and behavior in wildfires: Past research, current challenges and a future research agenda

Kuligowski, Erica D.

doi:10.1016/j.firesaf.2020.103129

Cited by 70 publications

(34 citation statements)

References 45 publications

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“…It is acknowledged that this simulation, while incorporating past behavioral data, could be continuously improved with greater realism. This might also include how demographic characteristics affect the decision to evacuate or stay/defend; see Toledo et al ( 6 ), Lovreglio et al ( 7 ), McCaffrey et al ( 8 ), Wong et al ( 11 ) and Kuligowski ( 13 ). Most of these studies, however, have found that risk perceptions, not demographics, are better predictors of choice.…”

Section: Methodsmentioning

confidence: 99%

“…One important improvement over the years has been the collection of post-disaster wildfire evacuation survey data to inform these models, for example, Wong et al ( 1 ), Toledo et al ( 6 ), Lovreglio et al ( 7 ), McCaffrey et al ( 8 ), Strahan ( 10 ), and Wong et al ( 11 ). However, much less work has focused on decisions during the evacuation process (e.g., route, destination) ( 11 , 12 ), as noted in Kuligowski ( 13 ). Other work, such as de Araujo et al ( 14 ), notes that behavior such as extra-trip making, mobilization time, and background traffic can also affect evacuations.…”

Section: Literature Reviewmentioning

confidence: 99%

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Developing Transportation Response Strategies for Wildfire Evacuations via an Empirically Supported Traffic Simulation of Berkeley, California

Zhao

Wong

2021

Transportation Research Record: Journal of the Transportation R

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Government agencies must make rapid and informed decisions in wildfires to evacuate people safely. However, current evacuation simulation tools for resource-strapped agencies largely fail to compare possible transportation responses or incorporate empirical evidence from past wildfires. Consequently, this study employs online survey data from evacuees of the 2017 Northern California Wildfires ( n = 37), the 2017 Southern California Wildfires ( n = 175), and the 2018 Carr Wildfire ( n = 254) to inform a policy-oriented traffic evacuation simulation model. The simulation is tested for a hypothetical wildfire evacuation in the wildland-urban interface of Berkeley, California. The study focuses on variables including fire speed, departure time distribution, towing of items, transportation mode, GPS-enabled rerouting, phased evacuations (i.e., allowing higher-risk residents to leave earlier), and contraflow (i.e., switching all lanes away from danger). It was found that reducing evacuating household vehicles (i.e., to one vehicle per household) and increasing GPS-enabled rerouting (e.g., 50% participation) lowered exposed vehicles (i.e., total vehicles in the fire frontier) by over 50% and evacuation time estimates (ETEs) by about 30% from baseline. Phased evacuations with a suitable time interval reduced exposed vehicles most significantly (over 90%) but produced slightly longer ETEs. Both contraflow (on limited links because of resource constraints) and slowing fire speed were effective in lowering number of exposed vehicles (around 50%), but not ETEs. Extended contraflow can reduce both exposed vehicles and ETEs. It is recommended that agencies develop a communication and parking plan to reduce the number of evacuating vehicles, create and communicate a phased evacuation plan, and build partnerships with GPS-routing services.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Developing Transportation Response Strategies for Wildfire Evacuations via an Empirically Supported Traffic Simulation of Berkeley, California

Zhao

Wong

2021

Transportation Research Record: Journal of the Transportation R

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“…However, evacuations can become complicated as the fire spreads. In addition, effective evacuations require specific protocols to be followed that the population may not be familiar with, causing complications when protecting people in emergencies [31]. Forest firefighters and rescue teams use various tools to control and fight forest fires, both physical and digital.…”

Section: Tools For Fighting Wildfiresmentioning

confidence: 99%

Outside Dynamic Evacuation Routes to Escape a Wildfire: A Prototype App for Forest Firefighters

et al. 2021

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This paper describes a prototype application to use different algorithms for creating optimal evacuation routes in the presence of a wildfire with a dynamic event-based update. The application uses a meteorological API that obtains real-time temperature, atmospheric pressure, humidity, speed, and wind direction of each location within an area using geographic coordinates (latitude and longitude) for creating a sensor network. The data are stored in a database for monitoring and visualization using the open-source platform Grafana, which includes an early warning mechanism that sends messages when it detects a temperature outside the normal range. Three different simulation scenarios were evaluated, varying the fire’s starting point coordinates and the evacuation route. The results show that the algorithm reacts to the presence of fire, maximizing safety margins even on longer evacuation routes. The prototype can be used to create an application to fight forest fires and safeguard rescue agents’ lives.

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“…Data: A Brief Review Existing studies of wildfire evacuation decision-making and departure timing are mainly based on non-GPS data, e.g., surveys, interviews, and traffic counts (Grajdura et al, 2021;Kuligowski, 2021;McCaffrey et al, 2018;McLennan et al, 2019;Strahan and Watson, 2019;Toledo et al, 2018;Vaiciulyte et al, 2021;Wong et al, 2020a,b;Woo et al, 2017). For example, Toledo et al (2018) conducted a survey study to analyze the choice whether or not to evacuate and related decisions during a wildfire event that occurred in Haifa Israel.…”

Section: Assessing Wildfire Evacuation Decision-making and Departure ...mentioning

confidence: 99%

“…Nevertheless, significant research gaps remain regarding the study of large-scale evacuation behavior, largely due to data limitations. To date, research on wildfire evacuation behavior has commonly relied on data collection methods such as surveys, interviews, and focus groups, e.g., (Kuligowski, 2021;McCaffrey et al, 2018). While these studies have generated valuable insights on many aspects of household behavior during wildfires, these empirical data have limitations.…”

Section: Introductionmentioning

confidence: 99%

Estimating Wildfire Evacuation Decision and Departure Timing Using Large-Scale GPS Data

Zhao¹,

Xu²,

Lovreglio³

et al. 2021

Preprint

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With increased frequency and intensity due to climate change, wildfires have become a growing global concern. This creates severe challenges for fire and emergency services as well as communities in the wildland-urban interface (WUI). To reduce wildfire risk and enhance the safety of WUI communities, improving our understanding of wildfire evacuation is a pressing need. To this end, this study proposes a new methodology to analyze human behavior during wildfires by leveraging a large-scale GPS dataset. This methodology includes a home-location inference algorithm and an evacuation-behavior inference algorithm, to systematically identify different groups of wildfire evacuees (i.e., self-evacuee, shadow evacuee, evacuee under warning, and ordered evacuee). We applied the methodology to the 2019 Kincade Fire in Sonoma County, CA. We found that among all groups of evacuees, self-evacuees and shadow evacuees accounted for more than half of the evacuees during the Kincade Fire. The results also show that inside of the evacuation warning/order zones, the total evacuation compliance rate was around 46% among all the categorized people. The findings of this study can be used by emergency managers and planners to better target public outreach campaigns, training protocols, and emergency communication strategies to prepare WUI households for future wildfire events.

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Evacuation decision-making and behavior in wildfires: Past research, current challenges and a future research agenda

Cited by 70 publications

References 45 publications

Developing Transportation Response Strategies for Wildfire Evacuations via an Empirically Supported Traffic Simulation of Berkeley, California

Developing Transportation Response Strategies for Wildfire Evacuations via an Empirically Supported Traffic Simulation of Berkeley, California

Outside Dynamic Evacuation Routes to Escape a Wildfire: A Prototype App for Forest Firefighters

Estimating Wildfire Evacuation Decision and Departure Timing Using Large-Scale GPS Data

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