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

By Xiang Yan, J. Levine, Xilei Zhao. Transportation Research Part C: Emerging Technologies, 2019

221 citations recorded by the source corpus.

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.

Subfields: Automotive Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/0cac5f17618bd2ce7b806c67b63f82e03e2892da

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Pascal Van Hentenryck
2. Yiyo Kuo
3. Russell W. Bent

In Transportation

1. Xiang Yan
2. Alan Yu
3. Xilei Zhao
4. Pascal Van Hentenryck

Citations in the corpus

• Mobility-on-demand versus fixed-route transit systems: An evaluation of traveler preferences in low-income communities (2019, background): “…services, with large-volume mass transit (trains and buses) efficiently servicing high-demand corridors while on-demand ridesourcing services covering low-density areas and filling first-and last-mile service gaps (Mah ´ eo et al., 2017; Stiglic et al., 2018; Yan et al., 2019; Shen et al., 2018).”
• Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models (2020, background): “A more detailed descriptions of the survey can be found in Yan et al. (2019).”