Exploring the Use of Crowdsourced Data Sources for Pedestrian Count Estimations

Counts provide the foundation for measuring nonmotorized travel along a link or a network and are also useful for monitoring trends, planning new infrastructure, and for conducting safety, health, and economic analyses. For safety analysis, they are critical in assessing the exposure to risk. Over the last decade, several automated technologies have been developed to count bicyclists and pedestrians. Despite advances in counting technology, cost and other considerations will continue to limit direct observation to small subsets of entire networks, as is the case for motorized traffic. A primary limitation with these counters is that they can only provide information about the activity that is directly on or near them but nothing about the activity on the network. The lack of widely available pedestrian count data precludes safety studies and analysis of trends, which has become critically important especially with the nationwide increase in pedestrian crashes over the last decade. The emergence of crowdsourced data such as Strava and StreetLight has allowed for the collection of large-scale datasets over broad areas of the network. While several research studies have evaluated and applied bicycle data from these datasets, no study has yet looked at pedestrian count estimates from these data sources or assessed how these compare to traditional pedestrian counts and other measures of pedestrian activity such as pedestrian actuations from traffic signals. The current study will evaluate pedestrian data estimates from the crowdsourced data sets and explore how these can be used along with traditional count data and sociodemographic data to derive count estimates.


  • English


  • Status: Active
  • Funding: $165000
  • Contract Numbers:



  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    TREC at Portland State University

    1900 SW Fourth Ave, Suite 175
    P.O. Box 751
    Portland, Oregon  United States  97201
  • Performing Organizations:

    Portland State University

    Department of Civil and Environmental Engineering
    Engineering Bldg, 301D, 1930 SW 4th Ave.
    Portland, OR  United States  97201

    University of Texas at Arlington

    Department of Civil Engineering
    Box 19308
    Arlington, TX  United States  76019
  • Principal Investigators:

    Kothuri, Sirisha

    Hyun, Kate

    Mattingly, Stephen

    McNeil, Nathan

  • Start Date: 20211001
  • Expected Completion Date: 20240630
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01781407
  • Record Type: Research project
  • Source Agency: National Institute for Transportation and Communities
  • Contract Numbers: NITC-1489, 69A3551747112
  • Files: UTC, RIP
  • Created Date: Sep 7 2021 10:38PM