Integrating ridesourcing services with public transit: An evaluation of traveler responses combining revealed and stated preference data

Abstract Inspired by the success of private ridesourcing companies such as Uber and Lyft, transit agencies have started to consider integrating ridesourcing services (i.e. on-demand, app-driven ridesharing services) with public transit. Ridesourcing services may enhance the transit system in two major ways: replacing underutilized routes to improve operational efficiency, and providing last-mile connectivity to extend transit’s catchment area. While an integrated system of ridesourcing services and public transit is conceptually appealing, little is known regarding whether and how consumers might use a system like this and what key service attributes matter the most to them. This article investigates traveler responses to a proposed integrated transit system, named MTransit, at the University of Michigan Ann Arbor campus. We conducted a large-sample survey to collect both revealed preference (RP) and stated preference (SP) data and fit a RP-SP mixed logit model to examine the main determinants of commuting mode choice. The model results show that transfers and additional pickups are major deterrents for MTransit use. We further applied the model outputs to forecast the demand for MTransit under different deployment scenarios. We find that replacing low-ridership bus lines with ridesourcing services could slightly increase transit ridership while reducing operations costs. The service improvements offered by ridesourcing mainly come from reductions in wait time. Though relatively small in our study, another source of improvement is the decrease of in-vehicle travel time. Moreover, we find that when used to provide convenient last-mile connections, ridesourcing could provide a significant boost to transit. This finding verifies a popular notion among transit professionals that ridesourcing services can serve as a complement to public transit by enhancing last-mile transit access.