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Measuring and modeling behavioral decision dynamics in collective evacuation
Jean M Carlson1, David L Alderson2, Sean P Stromberg1
1Department of Physics, University of California Santa Barbara, Santa Barbara, California, United States of America.
Plos One
|February 13, 2014
Summary
This study quantifies factors influencing human evacuation decisions during disasters. A new model captures collective behavior, aiding disaster response strategies.
Area of Science:
- Behavioral Network Science
- Decision Making
- Disaster Response
Background:
- Human decision-making factors are critical for system performance but remain challenging to quantify.
- System failures are often linked to human factors like congestion, overload, miscommunication, and delays.
- Understanding individual and collective responses in crisis situations is vital for effective disaster management.
Purpose of the Study:
- To quantify key factors influencing individual evacuation decision-making in a natural disaster scenario.
- To develop a quantitative model of human decision-making based on empirical evacuation data.
- To assess the impact of information sources (broadcast vs. peer-to-peer), temporal urgency, and shelter capacity on evacuation behavior.
Main Methods:
- Conducted a behavioral network science experiment in a controlled laboratory setting.
- Measured the cumulative rate of evacuations as a function of instantaneous disaster likelihood.
- Developed and validated a quantitative decision-making model against observed collective behavior.
Main Results:
- Quantified key factors affecting individual evacuation decisions, including information source, urgency, and capacity constraints.
- Developed a predictive model that accurately captures main features of collective evacuation behavior across scenarios.
- The model demonstrates sensitivity to external pressures and identifies variability in collective responses.
Conclusions:
- Robust methods for quantifying human decisions under risk are essential for disaster policy.
- Findings support the development and testing of evacuation strategies that integrate human behavior and network topology.
- This research provides a quantitative basis for improving disaster preparedness and response.
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