St. Thomas students draw rider-ready results from Metro Transit data
CommunityMetro Transit, St. Paul, MN
Community Size733,098 (2018 Census Estimation)
UniversityUniversity of St. Thomas
ProgramSustainable Communities Partnership
Case TypeProject Stories
School SizeGreater than 5000
Focus AreasEconomic and Social Inclusion
DisciplineEconomics, Research, Statistics
RegionEPA Region 5, USA
As the Twin Cities’ 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 “engage the community in [its] decision making…provide well crafted communication and offer opportunities for public involvement” (Mission Statement). 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 EPIC-Network, their unique program was a perfect match to meet Metro Transit’s 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 “two 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.” Their research was conducted as part of DataCom 2018, an annual data analysis competition sponsored by the Department of Economics which asks students to “analyze real-world data to answer their own research questions” (DataCom website). 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 EPIC 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’ participation in data analysis, Metro Transit and SCP engaged key issues impacting future riders, city planners, and transit workers.