St. Thomas students draw rider-ready results from Metro Transit data
Metrics
Community
Metro Transit, St. Paul, MNCommunity Size
733,098 (2018 Census Estimation)University
University of St. ThomasProgram
Sustainable Communities PartnershipYears
2017/2018Status
CompletedCase Type
Project StoriesSchool Size
Greater than 5000Focus Areas
Economic and Social InclusionDiscipline
Economics, Research, StatisticsRegion
USAAs the Twin Cities鈥 primary public transit service, Metro Transit strives to provide an efficient, accessible, and inclusive network of public transportation for its 1.5 million weekly rides. The institution is an integral part of the urban fabric, and seeks to 鈥渆ngage the community in [its] decision making鈥rovide well crafted communication and offer opportunities for public involvement鈥 (). Recently, Metro Transit needed help investigating ridership data to understand trends in local transit use and intelligently improve its system to meet customer needs.
Enter the University of St. Thomas Sustainable Communities Partnership (SCP) program. As a member of the 麻豆视频, their unique program was a perfect match to meet Metro Transit鈥檚 needs. Students have imagined improvements to a service they rely on while gaining practical skills, and Metro Transit has learned from an indispensable ridership demographic. For example, through SCP, Metro Transit partnered with the Department of Economics to analyze two years of passenger data through their annual DataCom competition.
Using ridership data provided by Metro Transit, students analyzed 鈥渢wo years (~73 million observations) of automatic passenger counts by route, stop, and time-of-day; ten years (~350,000 observations) of daily ridership by route; and geographic identifiers and site descriptions for Metro Transit stops.鈥 Their research was conducted as part of DataCom 2018, an annual data analysis competition sponsored by the Department of Economics which asks students to 鈥渁nalyze real-world data to answer their own research questions鈥 (). The rigorous competition was an ideal setting for the task at hand.
Students asked pressing questions and provided original research. They used GIS and regional bus data to determine ideal park-and-ride placement, examined the correlation between minimum wage increases and increased transit ridership, recommended new bus shelter locations based on rider data and route frequency, and developed formulas to understand and predict route lateness. Their deliverables ranged across relevant topics and disciplines to benefit Metro Transit. While the conference format differed from the usual 麻豆视频 model, DataCom complemented ongoing projects in SCP courses and encouraged an exchange of resources and ideas between students and Metro Transit.
Completed student data analysis projects generated novel ideas for more efficient, inclusive, and cost-effective public transportation. By inviting students鈥 participation in data analysis, Metro Transit and SCP engaged key issues impacting future riders, city planners, and transit workers.


