The safety impacts of pedestrian delay at signalized intersections

Pedestrian delay is widely associated with non-compliance and risky crossing behavior, yet few studies have linked delay directly to pedestrian crash outcomes. Using automated traffic signal performance measure (ATSPM) data and pedestrian crashes from more than 3,000 signalized intersections in Georgia, this study integrates probability-based, count-based, and economic models to quantify how delay influences pedestrian safety. A Wilcoxon signed-rank test, which controlled for roadway scale and speed limit by comparing high-delay and low-delay groups within geometrics blocks, confirmed that pedestrian delay is a significant factor associated with thru-movement and left-turn crashes (p < 0.01). Following this, multivariate logistic and negative binomial regression models were used to isolate the effects of delay while controlling for roadway geometry and pedestrian exposure (measured by the number of pedestrian push button activations). These results were integrated into an economic cost model to provide agencies with a data-driven tool for quantifying the safety and societal benefits of signal timing optimizations. Based on the analysis, for a 30 s increase in average pedestrian delay, the odds of a thru-movement vs pedestrian crash increase by 23%, and the odds of a left-turn crash increase by 39%. While delay, roadway geometry, and actuation frequency drive the likelihood of a crash occurrence, speed remains the primary determinant of severity; intersections with speed limits above 35 mph experience a 41.2% increase in the odds of a fatal or serious injury (FSI) outcome. Together, these probability, count, and cost frameworks provide transportation agencies with a unified, data-driven approach for identifying high-risk intersections and quantifying the safety and economic benefits of reducing pedestrian delay within Vision Zero and Safe System frameworks.