Collective Decision Dynamics In Group Evacuation

Quantifying uncertainties in collective human behavior and decision making is crucial for ensuring public safety, enabling effective disaster response, informing the design of transportation networks, and guiding the development of new technologies. However, modeling and predicting such behavior is notoriously difficult due to the influence of a variety of complex factors, including risk, time pressure, and the interaction and influence of social groups. We develop a stochastic model of human decision making to describe the empirical behavior of subjects in a controlled experiment simulating a natural disaster scenario. In particular, we quantify the influence of key factors, such as the reported disaster threat level, on individual decision strategies, and use these results to simulate and predict population-level behavior. Additionally, we use model simulations to compare individual evacuation decisions to those that require a group consensus, capturing strategy changes and tradeoffs that arise when decisions are made in a group context.