Automatic Counting of Pedestrians and Cyclists

Although the health and environmental benefits of a non-automobile commute are well known, it is still difficult to understand how to get more people to take up active transportation. Infrastructure can have a dramatic effect on cycling and walking adoption, but represents a significant outlay of government resources. Thus, concrete usage statistics are paramount for assessing and optimizing such spending. The goal of this project is to provide actionable data for government officials and advocates that promote bicycling and walking. The project created a vision-based cyclist and pedestrian counting system that allows for automatic and human-assisted data collection and analysis. The pedestrian and cyclist counting project was a result of a real-world need from the City of Pittsburgh to determine the usage of newly-created dedicated bike lanes throughout the city. Due to the relatively large area of bike paths for which it would be desirable to obtain information, a portable data collection system was deemed the most effective solution. The developed data collection device consists of a ruggedized Windows tablet, an extensible pole, and a miniature bullet camera. In order to collect data, the bullet camera is mounted at the top of the pole, which is extended to a suitable height. The whole system is fastened to a lamp post or other sturdy city fixture. The tabled is used to verify that the camera is pointed accurately at the bike lane and to control the data collection. The system is battery powered and allows for the collection of up to 12 hours of data on a full charge.

  • Record URL:
  • Supplemental Notes:
    • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
  • Corporate Authors:

    Technologies for Safe and Efficient Transportation University Transportation Center

    Carnegie Mellon University
    Pittsburgh, PA  United States  15213

    Research and Innovative Technology Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Pires, Bernardo R
    • Gong, Jian
    • Kaffine, Chris
    • Kocamaz, Mehmet Kemal
    • Kozar, John
    • Nunnagoppula, Ganesh Kumar
    • Saksena, Dhruv
  • Publication Date: 2016

Language

  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Research Report
  • Features: Figures; Photos; References; Tables;
  • Pagination: 11p

Subject/Index Terms

Filing Info

  • Accession Number: 01603627
  • Record Type: Publication
  • Contract Numbers: DTRT12GUTG11
  • Files: UTC, TRIS, RITA, ATRI, USDOT
  • Created Date: May 27 2016 9:44AM