Are travelers substituting between transportation network companies (TNC) and public buses? A case study in Pittsburgh

Document Type

Journal Article

Publication Date


Subject Area

place - north america, place - urban, mode - bus, mode - demand responsive transit, ridership - behaviour, ridership - demand, planning - service level


Transportation network companies (TNC), Ride hailing, Shared mobility, Travel behavior, Uber, Lyft


Transportation network companies (TNC) provide mobility services that are influencing travel behavior in unknown ways due to limited TNC trip-level data. How they interact with other modes of transportation can have direct societal impacts, prompting appropriate policy intervention. This paper outlines a method to inform such policies through a data-driven approach that specifically analyzes the interaction between TNCs and bus services in Pittsburgh, PA. Uber surge multiplier data is used over a 6-month time period to approximate TNC usage (i.e., demand over supply ratio) for ten predefined points of interest throughout the city. Bus boarding data near each point of interest is used to relate TNC usage. Data from multiple sources (weather, traffic speed data, bus levels of service) are used to control for conditions that influence bus ridership. We find significant changes in bus boardings during periods of unusually high TNC usage at four locations during the evening hours. The remaining six locations observe no significant change in bus boardings. We find that the presence of a dedicated bus way transit station or a nearby university (or dense commercial zones in general) both influence ad-hoc substitutional behavior between TNCs and public transit. We also find that this behavior varies by location and time of day. This finding is significant and important for targeted policies that improve transportation network efficiency.


Permission to publish the abstract has been given by SpringerLink, copyright remains with them.