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Machine learning -- Applications to local transit planning, Twitter, Choice of transportation -- United States --Planning, Travel time (Traffic engineering)


With today’s profusion of open data sources and real-time feeds, transit agencies have an unparalleled opportunity to leverage large amounts of data to improve transit service. Thanks to NITC researchers, there is now an open-source tool for that.

The new Social-Transportation Analytic Toolbox (STAT) for Transit Networks, developed by researchers at the University of Utah and Portland State University, is a dynamic platform that combines Twitter, general transit feed specification (GTFS), and census transportation planning products (CTPP)—in this case, job density data—to help agencies evaluate overall system performance and identify connectivity gaps. It can also act as a decision support tool for recommending service improvements.


This is a summary of TREC research project NITC-RR-1080, which can be found online at:

Report NITC-RR-1080 can be found at:

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