Exploring the stop sign running at all-way stop-controlled intersections with the SHRP2 naturalistic driving data.

Introduction: All-way stop control (AWSC) has been widely used at unsignalized intersections in the United States for its safety effects. However, many drivers do not make a complete stop before stop signs in practice (i.e., stop sign running), which presents safety concerns.

Method: This study explores driver behaviors at AWSC intersections with the SHRP2 naturalistic driving data.

Results: First, it is found that the full-stop rate is only 20.2% at AWSC intersections. Then, the study quantitatively analyzes what factors might influence the stop sign running decisions at AWSC intersections, where driver, vehicle, intersection geometry, maneuver, and environmental features are taken into account. In addition, considering the possible unobserved heterogeneities across drivers and intersections, a logistic regression model with both driver and intersection random effects is adopted. The results show that young and older drivers are less likely to fully stop, but there is no gender difference found. SUVs and vans are less likely to fully stop, drivers are less likely to fully stop at 3-leg intersections, and drivers are more likely to fully stop in daytime and weekdays. In terms of maneuvers, left-turn traversals are more likely to make a complete stop. In addition, both the driver and intersection random effects are found to be significant, vary greatly by individuals, and can be used to identify the few but critical high-risk drivers/intersections.

Practical Applications: The findings are expected to provide new insights for transportation agencies to formulate effective measures to deter stop sign running.