TITLE:
Analysis of Stopping Behavior at Rural T-Intersections Using Naturalistic Driving Study Data
AUTHORS:
Nicole Oneyear, Shauna Hallmark, Amrita Goswamy, Raju Thapa, Guillermo Basulto-Elias
KEYWORDS:
Naturalistic Driving Study Data, Intersection, Safety, Rural, Stopping Behavior
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.13 No.2,
April
7,
2023
ABSTRACT: Rural intersections account
for around 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood
safety problem. Crashes at rural intersections are also problematic since high
speeds on intersection approaches are present which can exacerbate the impact
of a crash. Additionally, rural areas are often underserved with EMS
services which can further contribute to negative crash outcomes. This paper
describes an analysis of driver stopping behavior at rural T-intersections using the SHRP 2 Naturalistic Driving Study data.
Type of stop was used as a safety surrogate measure using full/rolling
stops compared to non-stops. Time series traces were obtained for 157 drivers
at 87 unique intersections resulting in 1277 samples at the stop controlled
approach for T-intersections. Roadway (i.e. number of lanes, presence of
skew, speed limit, presence of stop bar or other traffic control devices),
driver (age, gender, speeding), and environmental characteristics (time of day,
presence of rain) were reduced and included as independent variables. Results
of a logistic regression model indicated
drivers were less likely to stop during the nighttime. However presence of
intersection lighting increased the likelihood of full/rolling stops. Presence
of intersection skew was shown to negatively impact stopping behavior.
Additionally drivers who were traveling over the posted speed limit upstream
of the intersection approach were less likely to stop at the approach stop
sign.