Estimating Inefficiency in Bus Trip Choices From a User Perspective With Schedule, Positioning, and Ticketing Data

The availability of historical data on the global positioning systems’ trajectories of vehicles and passenger boarding information for public bus fleets of large municipalities has given researchers and practitioners the opportunity to explore new challenges regarding the analysis of public transportation systems. This paper performs one such analysis as a case study examining the margin of improvement that passengers of a 1.8M people Brazilian city have when choosing their daily bus trips. In doing so, we document a number of not readily apparent challenges that must be overcome to leverage public transportation big data to policymakers, transportation systems operators, and citizens. Solutions are devised to each of these challenges and demonstrated on the analysis of the aforementioned 1.8M people city.