A novel stochastic agent-based model of building occupancy

We propose a novel stochastic agent-based model of occupancy dynamics in a building with an arbitrary number of zones and occupants. Simulation of the model yields time series of the location of each agent (occupant) over time, from which a time-series of occupancy (number of people in each zone) can be determined. The model is meant to provide realistic simulation of occupancy dynamics in non-emergency situations, which can be used for extraction of reduced order models of occupancy dynamics for estimation and control purposes. Comparison of the model´s prediction of mean occupancy, and distributions of random variables such as first arrival time, are provided against those estimated from measurements in a commercial building.