The Promise and Limitations of Locational App Data for Origin-Destination Analysis: A Case Study

Large, passively collected datasets from location-based services are a potential asset to transportation planning and modeling. These data have near-real-time availability and can capture travel behavior of a wide swath of the population. These data clearly hold promise for multiple transportation modeling methods, but practitioners should be aware of and account for various biases and other gaps inherent to the data. This volume seeks to further understand these gaps by comparing data from one large passively-collected data provider, Cuebiq, to data collected during a smartphone-based Global Positioning System (GPS) household travel survey. As part of this comparison, the authors developed an algorithm to infer trips from the Cuebiq location data and identified smartphone users present in both datasets. Results from this comparison identify potential gaps in Cuebiq’s representation of travel behavior, including demographic biases regarding traveler age and income and a bias toward trips longer than 9 miles (15 kilometers). The comparison also highlights the promising capability to capture detailed location behavior for a wide swath of the population, given the Cuebiq dataset’s pervasive spatial coverage. This volume also summarizes persisting uncertainties regarding data from location-based services and describes potential future work to measure and account for inherent biases as these data are introduced to planning and modeling applications.

  • Record URL:
  • Supplemental Notes:
    • Date on cover: April 2018.
  • Corporate Authors:

    RSG, Incorporated

    55 Railroad Row
    White River Junction, VT  United States  05001

    Federal Highway Administration

    Office of Planning, Environment and Realty
    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Adler, Thomas
    • Bernardin, Vince
    • Dumont, Jeff
    • Flake, Leah
    • Sadrsadat, Hadi
  • Publication Date: 2017-10

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Appendices; Figures; Maps; Tables;
  • Pagination: 40p

Subject/Index Terms

Filing Info

  • Accession Number: 01787249
  • Record Type: Publication
  • Report/Paper Numbers: FHWA-HEP-20-022
  • Contract Numbers: DTFH61-12-D-00013
  • Files: NTL, TRIS, ATRI, USDOT
  • Created Date: Nov 3 2021 11:46AM