Abstract

A deeper understanding of how weather variables affect pedestrian volumes is important, as active travelers are an essential part of a sustainable transportation system. Pedestrian data are limited for investigating the impacts of weather on walking levels, with most studies having data at only a couple of locations. Pedestrian actuation data (from push-buttons at traffic signals) overcomes this limitation. The Utah Department of Transportation archives pedestrian push-button press data for use in its Automated Traffic Signal Performance Measures system. In this study, pedestrian actuation data was used as a proxy for walking activity and weather data was collected from the National Oceanic and Atmosphere Administration. Using 15 months of daily time series data in Cache County, the impacts of weather on pedestrian signal activity were examined at 49 signalized intersections, using a log-linear time series regression analysis with categorical step-wise weather variables. The findings revealed that snow depth had the most frequent negative effect on walking activity. Snowfall (> 0.6 in.) also tended to have negative impacts when significant. Very hot maximum temperatures (≥ 90°F) were associated with lower pedestrian activity at around one-third of signals. Very low minimum temperatures (< 20°F) were also associated with lower pedestrian activity. Precipitation had a negative effect on walking levels, but at only a few signals. The study’s key findings offer implications for multimodal transportation planning (winter maintenance, shade trees, etc.) and traffic signal operations.

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