When to Commute During the COVID-19 Pandemic and Beyond: Analysis of Traffic Crashes in Washington, D.C

dc.contributor.authorChoi, Joanne
dc.contributor.authorClark, Sam
dc.contributor.authorJaiswal, Ranjan
dc.contributor.authorKirk, Peter
dc.contributor.authorJayaraman, Sachin
dc.contributor.authorAshqar, Huthaifa
dc.date.accessioned2024-12-11T17:02:42Z
dc.date.available2024-12-11T17:02:42Z
dc.date.issued2024-11-08
dc.description.abstractMany workers in cities across the world, who have been teleworking because of the COVID-19 pandemic, are expected to be back to their commutes. As this process is believed to be gradual and telecommuting is likely to remain an option for many workers, hybrid model and flexible schedules might become the norm in the future. This variable work schedules allows employees to commute outside of traditional rush hours. Moreover, many studies showed that commuters might be skeptical of using trains, buses, and carpools and could turn to personal vehicles to get to work, which might increase congestion and crashes in the roads. This study attempts to provide information on the safest time to commute to Washington, DC area analyzing historical traffic crash data before the COVID-19 pandemic. It also aims to advance our understanding of traffic crashes and other relating factors such as weather in the Washington, DC area. We created a model to predict crashes by time of the day, using a negative binomial regression after rejecting a Poisson regression, and additionally explored the validity of a Random Forest regression. Our main consideration for an eventual application of this study is to reduce crashes in Washington DC, using this tool that provides people with better options on when to commute and when to telework, if available. The study also provides policymakers and researchers with real-world insights that decrease the number of traffic crashes to help achieve the goals of The Vision Zero Initiative adopted by the district.
dc.description.urihttp://arxiv.org/abs/2411.05957
dc.format.extent16 pages
dc.genrejournal articles
dc.genrepreprints
dc.identifierdoi:10.13016/m2hptv-bgu8
dc.identifier.urihttps://doi.org/10.48550/arXiv.2411.05957
dc.identifier.urihttp://hdl.handle.net/11603/37096
dc.language.isoen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Data Science
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Engineering Management
dc.rightsAttribution 4.0 International CC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectStatistics - Computation
dc.subjectComputer Science - Computers and Society
dc.titleWhen to Commute During the COVID-19 Pandemic and Beyond: Analysis of Traffic Crashes in Washington, D.C
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-6835-8338
dcterms.creatorhttps://orcid.org/0000-0002-4845-0102

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