Scalable validation of automated bicycle and pedestrian counters: evidence from Washington, D.C.
Year: 2025
Type: article
Abstract: • Developed a scalable method to validate automated bike and ped counters. • Found 12–15 manual hours are needed for reliable correction functions. • Validated counters had a 46% improvement in mean RMSE of automated counts. • Accuracy improves when validation is done during peak hours and non-rain conditions. • Seasonal effects differ for bicycle and pedestrian validation. Data from automated pedestrian and bicycle counters is important in planning for active transportation. Counter validation approaches vary, from spot checks at initial installation of individual counters to rigorous comparison with manual count data. Since best practices differ, the data validity from counters is often unknown. This study identifies (1) the minimum number of manual count hours needed to reliably validate automated counters and (2) key factors affecting the accuracy of correction functions. Findings suggest that using 12–15 hours of count data to validate automated counters is the point of diminishing returns to develop reliable correction functions across site volumes. Counters that passed our validation criteria were associated with a 46% decrease in mean RMSE. For bicycle counters, greater accuracy was associated with validation on warmer, non-summer days, during peak hours, and with no precipitation. For pedestrian counters, higher accuracy was associated with validation during summer, spring, or early winter with no precipitation.
Institutions: Virginia Tech, University of North Carolina at Chapel Hill
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,400
Award: G8869731703
OpenAlex ID: W4414822792
