Creating a better revenue model for MBTA

Massachusetts Bay Transportation Authority, a.k.a. MBTA, is the public transit agency operating most transit in the Greater Boston area, including busses, subways, and trains. The MBTA operates with high-level averages of revenue data, but does not have access to a detailed model of fares across different routes, times and dates, modes of transit, passenger profiles, and other characteristics. The goal of this project is to create a more granular cost model using existing passenger transaction data.

Such a model can be used to analyze bus route efficiency in greater detail than is currently possible, and then enable further exploration. We've received an initial data set of ~275 million "boardings" for MBTA subway and bus trips taken duringthe 2016 calendar year. Based on this dataset, and schedule information obtained from the MBTA’s publicGTFS API, we’ve completed some initial data exploration and built an initial revenue model.