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

Andy Berres, Brett Bass, Joshua R. New, Piljae Im, Marie Urban, Jibonananda Sanyal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publicationBS 2021 - Proceedings of Building Simulation 2021
Subtitle of host publication17th Conference of IBPSA
EditorsDirk Saelens, Jelle Laverge, Wim Boydens, Lieve Helsen
PublisherInternational Building Performance Simulation Association
Pages3616-3623
Number of pages8
ISBN (Electronic)9781775052029
DOIs
StatePublished - 2022
Event17th IBPSA Conference on Building Simulation, BS 2021 - Bruges, Belgium
Duration: Sep 1 2021Sep 3 2021

Publication series

NameBuilding Simulation Conference Proceedings
ISSN (Print)2522-2708

Conference

Conference17th IBPSA Conference on Building Simulation, BS 2021
Country/TerritoryBelgium
CityBruges
Period09/1/2109/3/21

Funding

This work was funded in part by field work proposal CEBT105 under US Department of Energy Building Technology Office Activity Number BT0305000, the Office of Electricity Activity Number TE1103000.

FundersFunder number
US Department of Energy Building TechnologyBT0305000, TE1103000

    Fingerprint

    Dive into the research topics of 'Generating traffic-based building occupancy schedules in Chattanooga, Tennessee from a grid of traffic sensors'. Together they form a unique fingerprint.

    Cite this