When Implementing Pedestrian and Bicycle Automated Count Technologies, Select and Design Sites with Widths Compatible with Detector Parameters and Avoid Unconstrained Locations to Mitigate Bypass Errors.
Automated Counting Technologies Tested in Virginia, Washington D.C., and California Sites Reveal Lessons for Accurately Capturing Pedestrian and Bicycle Volume Data.
Made Public Date

Methods and Technologies for Pedestrian and Bicycle Volume Data Collection: Phase 2


As pedestrian and bicycle volumes tend to be more variable than motor vehicle volumes, this study tested and evaluated five automated pedestrian and bicycle counters in different settings, including ranges of temperature, varying weather conditions, mixed traffic conditions, mixed travel directions, and facility types at test sites in Arlington, VA, Washington D.C., and Oakland, CA. The five tested devices represent four different technologies, namely: thermal imaging cameras with passive infrared sensors, radar, bicycle-specific pneumatic tubes, and piezoelectric strips. The study also tested standard pneumatic tubes.

The counter technologies were evaluated based on their accuracy of classifying bicycle and pedestrian volumes, ease of implementation, labor requirements, security from theft or vandalism, maintenance requirements, software requirements, cost, and flexibility of downloading and working with the count data. It should be noted that none of the tested products yielded perfect matches with the actual pedestrian and bicycle volumes; all required some calibration to the raw count data to produce better estimates.

Lessons Learned

  • Place counters strategically at the site to minimize bypass errors. Careful selection for the location of counters at the site plays an important role in the ultimate accuracy of the collected count data leaving no room for any instances where pedestrians or bicycles may end up staying outside the counter’s detection zone.    
  • Account for occlusion when using screenline sensor‐based technologies such as radio beam or passive infrared. Occlusion is an unavoidable and predictable factor contributing to systematic undercounting. The degree to which occlusion contributes to undercounting depends on pedestrian and bicycle grouping (i.e., groups of persons traveling side‐by‐side).
  • Calibrate the installed counters at specific sites for reliable results. It is critical for practitioners to calibrate the counters they install using site-specific parameters to obtain the most accurate and reliable results.                 
  • Adjust automated counts to reflect ground truth volumes. For passive infrared and radio beam sensors, undercounting may occur for pedestrians or bicycles moving side-by-side in groups. Controlling for such factors can be achieved by developing correction factors.
  • Create factor groups from sites with similar characteristics to use in data extrapolation. For identifying and extrapolating longer-duration counts from shorter-duration counts, a potential approach is      to create groups of sites that are considered similar in their pedestrian or bicycle volume peaking characteristics. Current standard guidance is to match short-term count sites with sites having continuous data in the same factor group to determine the appropriate factors for extrapolation.
  • Understand the difference between which factors may or may not have an impact on counting accuracy. No clear impact or effect were found for several factors that were anticipated to affect the accuracy of counting technologies in the testing, such as the age of inductive loops and pneumatic tubes, temperature, and rain and snow events. It is recommended to follow vendor‐specified practices for deployment and installations under varying weather conditions or climatic regions, as well as maintaining and replacing equipment.
  • Work directly with the vendor when using an automated count technology for the first time. Practitioners should work with the vendor to thoroughly understand the product’s installation, operation, and maintenance requirements, including those of any required accessories (e.g., software, communications equipment). As with any product, obtaining other users’ experiences with specific products and specific vendors’ customer support can also be highly useful when making decisions on which product(s) to purchase.
Goal Areas