Generating traffic-based building occupancy schedules in Chattanooga, Tennessee from a grid of traffic sensors

Abstract

Building occupancy significantly impacts energy use, timing for demand impacts, and is a significant source of uncertainty in building energy models. There are relatively few sources that define building occupancy schedules and number of occupants per building or space type. More importantly, these sources define traditional schedules that are likely not to reflect the true occupancy of a given building. We construct traffic-based occupancy schedules which are more responsive to changes in mobility patterns, and which can realistically estimate occupant arrivals, departures, and counts in individual buildings.