Urban Mobility Analysis

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dc.contributor.authorLeavitt, Brianen
dc.contributor.authorLuo, Oliveren
dc.contributor.authorMcCormick, Lukeen
dc.contributor.authorPark, Jamesen
dc.contributor.authorTran, Richarden
dc.date.accessioned2022-05-10T01:25:20Zen
dc.date.available2022-05-10T01:25:20Zen
dc.date.issued2022-05-04en
dc.description.abstractOur product allows for mobility analysis in the DMV area using demographic information as well as the change in ridership numbers for the DMV metro due to the Covid-19 lockdown in March 2020. Users can view demographic information such as household income and highest education attained for each census tract in the DMV area on an interactive map. The map also can display metro ridership information before and after the lockdown as well as the percent change in ridership numbers for each individual metro station. The website allows users to input their own data into a machine learning model which would predict post-lockdown DMV metro ridership based on the given demographic data and pre-lockdown-pandemic ridership numbers. This allows for insight on metro ridership if an event similar to the Covid-19 pandemic were to happen in the future.en
dc.description.notesAccess to our data can be found at our GitLab repository: https://code.vt.edu/cs-5934-spring-22/urban-mobility-analysisen
dc.identifier.urihttp://hdl.handle.net/10919/109978en
dc.language.isoen_USen
dc.rightsCC0 1.0 Universalen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.titleUrban Mobility Analysisen
dc.typePresentationen
dc.typeVideoen

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CS5934: Capstone Project