Enhancing indoor building occupant safety in the built environment: Assessing the validity of social force modeling for simulating physical distancing behaviors
DC Field | Value | Language |
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dc.contributor.author | Yoon, Inseok | - |
dc.contributor.author | Ahn, Changbum | - |
dc.contributor.author | Ahn, Seungjun | - |
dc.contributor.author | Lee, Bogyeong | - |
dc.contributor.author | Lee, Jongjik | - |
dc.contributor.author | Park, Moonseo | - |
dc.date.accessioned | 2024-03-06T09:30:21Z | - |
dc.date.available | 2024-03-06T09:30:21Z | - |
dc.date.issued | 2024-03 | - |
dc.identifier.issn | 2666-1659 | - |
dc.identifier.issn | 2666-1659 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/32716 | - |
dc.description.abstract | Facility managers play a key role in ensuring the safety of occupants in indoor environments, particularly in the event of a disaster. Pedestrian Simulation Models, such as the Social Force Model (SFM), are essential for simulating pedestrian behavior and evaluating safety measures in complex indoor environments. These models help to identify potential hazards and bottlenecks. However, concerns about the accuracy of the SFM in reproducing physical distance, particularly during the COVID-19 pandemic, have raised doubts about its reliability, but little attention has been paid to the validity of the SFM in analyzing human movement in indoor environments. Our study rigorously evaluates the applicability of SFM for simulating physical distancing behavior in indoor environments, using trajectory data from building occupants during the COVID-19 peak. The investigation compares standard SFM with Pandemic SFM, which is customized for physical distancing. The results clearly demonstrate the superior performance of Pandemic-SFM in replicating indoor occupant movement, particularly in crowded spaces. Sensitivity analysis highlights the importance of accurately modeling physical distancing, particularly during infectious disease outbreaks. These findings hold great promise for improving occupant behavior simulation models, especially in indoor building environments, and provide scientific evidence to guide safety improvements during pandemics. © 2024 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Elsevier Ltd | - |
dc.title | Enhancing indoor building occupant safety in the built environment: Assessing the validity of social force modeling for simulating physical distancing behaviors | - |
dc.type | Article | - |
dc.publisher.location | 네델란드 | - |
dc.identifier.doi | 10.1016/j.dibe.2024.100336 | - |
dc.identifier.scopusid | 2-s2.0-85183454461 | - |
dc.identifier.wosid | 001175582500001 | - |
dc.identifier.bibliographicCitation | Developments in the Built Environment, v.17 | - |
dc.citation.title | Developments in the Built Environment | - |
dc.citation.volume | 17 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Construction & Building Technology | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Construction & Building Technology | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.subject.keywordAuthor | COVID-19 | - |
dc.subject.keywordAuthor | Facility management | - |
dc.subject.keywordAuthor | Indoor safety | - |
dc.subject.keywordAuthor | Pedestrian modeling | - |
dc.subject.keywordAuthor | Safety measures | - |
dc.subject.keywordAuthor | Social force model | - |
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