Mobile ticketing apps have become increasingly popular among transit agencies due to their cost efficiency and ability to streamline payments. Beyond operational efficiencies, these apps also generate vast travel data with the potential to support transit agencies in decision-making. However, this data contains incomplete trip information and suffers from representation bias. Several questions remain unanswered: Is this data representative of all transit riders? If so, what are the potential applications?
This project will address this gap by evaluating the potential applications and representativeness of app data. The research will focus on ZipPass, a mobile ticketing app used by Unitrans in Davis, California. To date, ZipPass has already generated over one million spatial activation records. The project team devised a strategy to integrate ZipPass data with the onboard transit survey and the UC Davis campus travel survey. The team will also conduct a targeted survey of active ZipPass users to supplement rider-specific and trip-level information. The project will explore how ZipPass data, along with support from supplementary data sources, can be used for two potential applications to support the agency: (1) estimating transit ridership and (2) understanding riders' origin-destinations.
The research will provide valuable insights to transit agencies looking to harness mobile ticketing data for operational purposes. Since periodic onboard transit surveys are required for federal funding, both mobile ticketing data and transit survey data are available to agencies at no extra expense. Small agencies can leverage our findings to integrate at least these two datasets and effectively utilize them for operational improvement.
