PSAM 16 - Paper Overview

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Lead Author: Marilia Ramos Co-author(s): Mohammad Pishahang , mh.pishahang@risksciences.ucla.edu Enrique Andrés Lopez Droguett, eald@ucla.edu Ali Mosleh, mosleh@ucla.edu Andres Alfredo Ruiz-Tagle Palazuelos , aruiztag@umd.edu

Integrating Human Behavior Modeling into a Probabilistic Wildfire Egress Planning Framework
Wildland Urban Interface (WUI) can be defined as “the zone of transition between unoccupied land and human development.” The communities in these areas are particularly vulnerable to wildfires that start and propagate in wildlands. According to the U.S. Fire Administration, the U.S. has more than 70 thousand communities at risk for WUI fires, and the WUI area grows by approximately 2 million acres per year. Numerous efforts have been undertaken to address the dangers of wildfires, including building more resilient infrastructures, advancing techniques for extinguishing fires and exploring the possibilities of controlled fires. Associated with these efforts is the pressing need to ensure the safe evacuation of communities in WUI once they are threatened by wildfires. Evacuation modeling and planning is a challenging and complex problem. It involves human decisions and actions concerning if, when, and how to evacuate; directly impacting the traffic flow during the evacuation. Furthermore, the available time for a community to evacuate is a dynamic element: it changes according to the fire progression, which, in turn, depends on vegetation, weather, among other factors. The models for traffic and fire progression have advanced considerably in the past years. Human behavior modeling during wildfire evacuations has also received significant attention, leveraging existing studies for other natural hazards, such as hurricanes. However, these are mainly developed as standalone, qualitative approaches rather than integrated into a complete egress framework that accounts for traffic modeling and wildfire progression. This paper discusses the existing methods for modeling human behavior during wildfire evacuation and the requirements for such a model to be integrated into a quantitative, probabilistic evacuation planning tool. It further presents the method adopted for integrating human behavior model into the evacuation planning tool WISE (Wildfire Safe Evacuation). WISE calculates the probability of successful evacuations through a framework that incorporates human behavior, traffic, and fire progression models using Bayesian Networks, Agent-Based models, real-world socio-demographic data, and Geographic Information System. Finally, the paper showcases the impact of the socio-demographic profile of different communities on a safe evacuation probability.

Integrating Human Behavior Modeling into a Probabilistic Wildfire Egress Planning Framework

Wildland Urban Interface (WUI) can be defined as “the zone of transition between unoccupied land and human development.” The communities in these areas are particularly vulnerable to wildfires that start and propagate in wildlands. According to the U.S. Fire Administration, the U.S. has more than 70 thousand communities at risk for WUI fires, and the WUI area grows by approximately 2 million acres per year. Numerous efforts have been undertaken to address the dangers of wildfires, including building more resilient infrastructures, advancing techniques for extinguishing fires and exploring the possibilities of controlled fires. Associated with these efforts is the pressing need to ensure the safe evacuation of communities in WUI once they are threatened by wildfires. Evacuation modeling and planning is a challenging and complex problem. It involves human decisions and actions concerning if, when, and how to evacuate; directly impacting the traffic flow during the evacuation. Furthermore, the available time for a community to evacuate is a dynamic element: it changes according to the fire progression, which, in turn, depends on vegetation, weather, among other factors. The models for traffic and fire progression have advanced considerably in the past years. Human behavior modeling during wildfire evacuations has also received significant attention, leveraging existing studies for other natural hazards, such as hurricanes. However, these are mainly developed as standalone, qualitative approaches rather than integrated into a complete egress framework that accounts for traffic modeling and wildfire progression. This paper discusses the existing methods for modeling human behavior during wildfire evacuation and the requirements for such a model to be integrated into a quantitative, probabilistic evacuation planning tool. It further presents the method adopted for integrating human behavior model into the evacuation planning tool WISE (Wildfire Safe Evacuation). WISE calculates the probability of successful evacuations through a framework that incorporates human behavior, traffic, and fire progression models using Bayesian Networks, Agent-Based models, real-world socio-demographic data, and Geographic Information System. Finally, the paper showcases the impact of the socio-demographic profile of different communities on a safe evacuation probability.

Paper MA211 Preview

Author and Presentation Info

Lead Author Name: Marilia Ramos (marilia.ramos@ucla.edu)

Bio:

Country: United States of America
Company: University of California Los Angeles
Job Title: Research Scientist

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Paper MA211 Preview

Author and Presentation Info

Download paper MA211.