Virtual human crowd models have been used in the simulation of building and urban evacuation, but have not yet applied to underground coal mine operations and escape situations with emphasis on smoke, fires and physiological behaviors. We explore this through a real-time simulation model, MIMOSA (Mine Interior Model Of Smoke and Action), which integrates an underground coal mine virtual environment, a fire and smoke propagation model, and a human physiology and behavior model. Each individual agent has a set of physiological parameters as variables of time and environment, simulating a miner’s physiological condition during normal operations as well as during emergencies due to fire and smoke. To obtain appropriate agent navigation in the mine environment, we have extended the HiDAC framework (High- Density Autonomous Crowds) navigation from a grid-based cell-portal graph to a geometrybased portal path and integrated a novel cellportal and shortest path visibility algorithm.