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Evaluating the Relationship between the Driver and Roadway to Address Rural Intersection Safety using the SHRP2 Naturalistic Driving Study Data

Image: Overhead lighting on one side of the roadway at a stop-controlled rural intersection

Rural intersection lighting

Image: Evening view of overhead flashing yellow beacons upstream of a stop-controlled intersection

Overhead flashing yellow beacons upstream of stop-controlled intersection

Image: Rumble strips milled in the pavement across the upstream wheel paths shortly before a stop ahead sign

Wheel-path rumble strips and advance stop ahead sign (Image: Corkle, Marti, and Montebello for MnDOT)

Image: Dynamic conflict system to warn of entering traffic when pole-mounted beacon is flashing at a rural intersection

Rural intersection conflict warning system (MnDOT Traffic Engineering)


Principal investigators:

Co-principal investigators:

Project status


Start date: 07/01/13
End date: 02/28/16


Report: Evaluating the Relationship between the Driver and Roadway to Address Rural Intersection Safety using the SHRP 2 Naturalistic Driving Study Data (1.77 mb pdf) February 2016



About the research


Rural intersections account for 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood safety problem. Transportation agencies have traditionally implemented countermeasures to address rural intersection crashes but frequently do not understand the dynamic interaction between the driver and roadway and the driver factors leading to these types of crashes.

The Second Strategic Highway Research Program (SHRP2) conducted a large-scale naturalistic driving study (NDS) using instrumented vehicles. The study has provided a significant amount of on-road driving data for a range of drivers. The present study utilizes the SHRP2 NDS data as well as SHRP 2 Roadway Information Database (RID) data to observe driver behavior at rural intersections first hand using video, vehicle kinematics, and roadway data to determine how roadway, driver, environmental, and vehicle factors interact to affect driver safety at rural intersections.

A model of driver braking behavior was developed using a dataset of vehicle activity traces for several rural stop-controlled intersections. The model was developed using the point at which a driver reacts to the upcoming intersection by initiating braking as its dependent variable, with the driver’s age, type and direction of turning movement, and countermeasure presence as independent variables. Countermeasures such as on-pavement signing and overhead flashing beacons were found to increase the braking point distance, a finding that provides insight into the countermeasures’ effect on safety at rural intersections. The results of this model can lead to better roadway design, more informed selection of traffic control and countermeasures, and targeted information that can inform policy decisions.

Additionally, a model of gap acceptance was attempted but was ultimately not developed due to the small size of the dataset. However, a protocol for data reduction for a gap acceptance model was determined. This protocol can be utilized in future studies to develop a gap acceptance model that would provide additional insight into the roadway, vehicle, environmental, and driver factors that play a role in whether a driver accepts or rejects a gap.