Direct Ridership Model


Direct ridership models (DRMs) estimate transit ridership based on the built-environment and land use characteristics of station areas (e.g., population, housing, employment, and design), transit service features (e.g., the levels of train and bus services provided, and capacity of parking and park & ride facility), and sociodemographic characteristics of riders. DRMs have emerged in the United States as a low cost, quick alternative to traditional four-step travel demand models to forecast transit ridership at the station level.  They have been used to help evaluate Transit Oriented Development (TOD) potentials at existing and future rail station areas, formulate policy guidance for TODs, identify underperforming stations, and plan for long-range transit service planning. In an effort to advance the capacity of DRMs, NCSG developed the Origin-Destination Direct Transit Demand Model (OD-DTDM) to identify the determinants of transit demand between OD-station pairs of the Metrorail system of the Washington Metropolitan Area Transit Authority (WMATA) by time of day. This model is more advanced than previous station-level DRM as it utilizes the data collected through WMATA’s smartcard fare media (SmarTrip) and also examines the effects of fare, travel distance, and travel time by mode on the OD-station level Metrorail travel demand.  It also utilizes a more robust and rigorous statistical model.  Two of major applications of the NCSG’s OD-DTDM are: (a) estimation of ridership increase in response to increases in the number of households and jobs in TOD areas, and (b) estimation of the effects of fare structure changes on ridership and fare revenue.

NCSG has developed multiple DRMs for a number of major transportation and transit agencies in the U.S., including the Maryland Department of Transportation (MDOT), and Maryland Transit Administration (MTA), and WMATA. Some results have been incorporated into transit agencies’ pipeline planning process, future revenue projections, and rail service planning.

In the next phase of DRM development, the team will collaborate with transit agencies on model applications for policy evaluations and preparation for medium- and long-range planning. The team is also working on innovative ways of integrating DRMs to the state-wide travel demand models (MSTM) and advanced modeling techniques by integrating big data to investigate both temporal and spatial patterns of transit riders.







Team Leads

  • Hiro Iseki, Associate Professor, NCSG
  • Chao Liu, Faculty Research Associate, NCSG

Additional Team Members

  • Raynell Louis Cooper, NCSG
  • Rob Jones, PhD student, NCSG
  • Ting Ma, PhD student, NCSG
  • Pranita Ranbhise, Graduate Assistant, NCSG
  • Pranali Shetty, Graduate Assistant, NCSG
  • Sicheng Wang, visiting student, NCSG