RAPID: Fare Free Public Transportation - A Full Scale Natural Experiment in Alexandria, Virginia

University Of Maryland, College Park, College Park MD

Investigators

Abstract

This Grant for Rapid Response Research (RAPID) project will assess the effects of free public transit and improved network connectivity on ridership, miles driven by private vehicles, emissions of greenhouse gases and conventional pollutants, congestion and traffic, and will study its distributional effects on different income groups and ethnicities. The project is based on a full-scale natural experiment conducted in Alexandria, Virginia, where the local transit agency DASH (Driving Alexandria Safely Home) has decided to implement a fare-free public transportation program over its service territory, motivated primarily by fairness and equity considerations. Such a natural experiment will be based on a data collection the study area and from one or more control locations—while the program is in place, and retrospectively for a suitable period before its implementation—for a proper assessment of its accomplishments and effects. The survey plan will involve both users of the DASH system as well as members of the general public at the treatment location to understand actual or potential travel, general travel patterns, and whether the fare free has displaced private car travel and emissions, or other transportation modes. The data collection plan will be complemented with parallel surveys of transit users and members of the general public at the control locations to elicit similar information and their intended use of transit if the bus became free. This research and its results may influence policy recommendations and infrastructure investment decisions that will impact the future of our transportation system and the quality of life of citizens in America. The impacts from this project are especially relevant at this time, when transit use is slowly recovering from the pandemic and has not yet reached pre-pandemic ridership and travel mode shares, and when large-scale funding to infrastructure is being considered by this Administration and the Congress. From a methodological perspective, the study involves challenging statistical procedures in terms of sampling, analyzing, and modeling the data from both probabilistic and non-probabilistic samples. Challenges include the construction of sampling weights, the selection of control location, matching treated and control subjects to ensure valid statistical inference, and many others. A multi-disciplinary team composed by faculties and students in engineering, economics, survey methodology and mathematics will work collaboratively on survey design, data linkage, econometric model estimation, and travel behavior and policy analysis. The project is expected to be serving as a proof of concept for similar programs elsewhere and will be a reference for the many transit agencies implementing innovative policy schemes to increase ridership and accessibility. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.