Armed with a nearly $1.2 million National Science Foundation grant, UF, Johns Hopkins University and the University of Utah are creating these AI-based models to simulate human behavior during evacuations – information that will help emergency managers shape more effective evacuation plans.
“Strengthening wildfire resilience requires accurate modeling and a deep understanding of collective human behavior during evacuations,” said UF project lead Xilei Zhao, Ph.D., an associate professor with the Engineering School of Sustainable Infrastructure and Environment. “There is a critical need for simulation models that can realistically capture how civilians, incident commanders and public safety officials make protective decisions during wildfires.”
Existing simulation models face limitations, particularly with reliable predictions under various wildfire scenarios. New AI models can simulate how diverse groups of people behave and interact during the hurried scramble to seek safety.
Zhao’s team is developing a convergent AI framework for wildfire evacuation simulations powered by psychological theory-informed large language models. Using UF’s supercomputer HiPerGator, the team will produce simulation methods to promote teaching, training and learning, and support wildfire resilience by allowing public safety officials to use open-access tools.