The Washington Metropolitan Area Transit Authority (WMATA)’s fare structure is among the most complex in the United States: Fares for Metrorail services are unique to each station pair, customers (especially visitors) may end up on pass products that cost more than they need, and a variety of discounts are available based on transfer behavior and rider characteristics. This complexity made it difficult for WMATA to calculate expected revenue changes from fare products, let alone the consequent impacts to ridership, so the agency needed enhanced tools to understand how fare and service changes would affect ridership, revenue, and different types of riders.
Foursquare ITP developed a comprehensive fare and service modeling approach built on the GTFS Fares v2 specification, including new methods for estimating pass product selection when trip costs increase.
WMATA planners and analysts can now quickly estimate how fare changes affect ridership and revenue, including detailed breakdowns by rider demographic group and origin-destination pair.
The new approach is significantly faster and more flexible than WMATA’s previous model, which relied on Tableau to load data, perform calculations, and generate results.
Solutions and Outcomes
- Enhanced Python-based tools estimating revenue and ridership impacts by demographic group.
- Built fare modeling on the GTFS Fares v2 specification for future flexibility.
- Modeled fare product choice using historical SmarTrip tap data.