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ICTD 2025

Active Transportation (Bike/Ped)

Promoting a Robust Active Transportation System Through Traffic Control and Operations

Pedestrian Volumes from Push-Button Traffic Signal Data in Oregon

Tuesday, June 10, 2025
9:15 AM – 9:30 AM MT
Abstract: This study’s objective was to develop methods and assess their transferability in estimating pedestrian volumes from pedestrian push-button data. First, videos were recorded in Summer 2022 at 64 signalized intersections in Oregon, and pedestrian counts were extracted. Next, pedestrian traffic signal data were assembled for the same locations and time periods. After counting 41,843 crosswalk users from 2,679 hours of video, the final sample size was 8,546 observations, each representing one hour at one signalized crosswalk. For the data analysis, a multi-step process considered three dependent variables (different definitions of “pedestrians” or “crosswalk users”), eight single independent variables (pedestrian actuations and detections, modified to account for signal operations and push-button press behaviors), five functional forms (linear, quadratic, etc.), and 14 segmentation variables (representing signal operations, temporal factors, and built environment characteristics). The final recommended model had a quadratic relationship between total crosswalk users and the number of push-button presses, filtered to remove multiple presses within 15 seconds of another. The model’s predictions were strongly correlated (0.86) with observed pedestrian volumes and had a low average error of ±2.4 pedestrians per hour. Furthermore, when comparing the Oregon and Utah models and data, the remarkable consistency of the two state’s quadratic fit lines—collected in different states three years apart—gives some expectation of transferability for the developed model. Such pedestrian volume estimates could improve pedestrian traffic monitoring, safety assessments, and equity and health analyses.

Learning Objectives:

Attendees can expect to learn the following from this session:
  • To develop methods to estimate pedestrian volumes from pedestrian push-button data in Oregon.
  • To compare the best predictors and functional forms in estimating the number of pedestrians from the push-button data.
  • To measure the accuracy of using push-button data to predict pedestrian volumes.