Generating traffic-based building occupancy schedules in Chattanooga, Tennessee from a grid of traffic sensors
Sep 1, 2021·
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Andreas Berres
Brett Bass
Joshua R New
Piljae Im
Marie Urban
Jibonananda Sanyal
An overview of the methodology presented in this paper, guided by the data workflow. The left-hand side of the figure, (a)-(d), illustrates the traffic data workflow to determine the flow of people into and out of the area. The right-hand side of the figure, (f )-(h), illustrates the building workflow to identify the mapping from intersections to buildings, using Voronoi cells.Finally, the two workflows join at the bottom of the figure (e): the prospective building occupants for each intersection are distributed to its assigned buildings.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.
Type
Publication
In Proceedings of Building Simulation 2021: 17th Conference of IBPSA
