Results of the First Large-scale Survey of TNC Use in the Bay Area

Transportation Network Companies (TNCs) such as Uber and Lyft have grown tremendously over the past decade, particularly in the San Francisco Bay Area. Still, relatively little publicly available data exists about the users of these services, their travel behaviors, the volume of use, times and locations of TNC trips, and how TNC services are impacting transportation system performance overall. This paper describes the methods and descriptive results of the first large-scale smartphone-based TNC user survey conducted in the California Bay Area in fall 2018 and spring 2019. The study design took a standard household travel survey approach and optimized it to capture more TNC users and TNC travel behavior, using innovative methods to sample more TNC users via a targeted address-based sampling strategy and to capture more TNC trips by using a seven-day long travel period. The study also used innovative methods for the data weighting approach to ensure the resulting dataset was representative for the nine-county Bay Area across all days of the week. Lastly, the study methods were pre-tested and improved to facilitate a scalable project when applying the study methods to subsequent 2019 surveys in two other regions of California. The resulting datasets provide high quality data to support travel model estimation and calibration for trip and tour mode choice models, TNC user demographic profiles, and overall travel behavior analyses. The paper includes results describing mode shares, TNC trip purposes, TNC mode-choice substitution effects, and time-of-day and day-of-week travel patterns across the nine-county Bay Area.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 16p

Subject/Index Terms

Filing Info

  • Accession Number: 01764968
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-02320
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:25AM