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Evaluation of the Impact of Driver Behavior on Back of Queues Events in Work Zones Using the SHRP2 Naturalistic Driving Study Data

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Journal of Transportation Technologies 2024年第2期14卷 179-194页

作者： Shauna Hallmark Guillermo Basulto-Elias nicole oneyear Omar Smadi Institute for Transportation 2711 S. Loop Drive Suite 4700 Ames Iowa Iowa Division Federal Highway Administration Ames Iowa

The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE and 209 “normal” events which were used as controls. The traces included representing 209 unique drivers. A Mixed-Effects Logistic Regression model was developed with probability of a SCE as the response variable and driver and work zone characteristics as predictor variables. The final model indicated glances over 1 second away from the driving task and following closely increased risk of an SCE by 3.8 times and 2.9 times, respectively. Average speed was negatively correlated to crash risk. This is counterintuitive since in most cases, it is expected that higher speeds are related to back of queue crashes. However, most queues form under congested conditions. As a result, vehicles encountering a back of queue would be more likely to be traveling at lower speeds.

关键词： Safety Critical Events Speed Following Closely Glance Behavior

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Analysis of Stopping Behavior at Rural T-Intersections Using Naturalistic Driving Study Data

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Journal of Transportation Technologies 2023年第2期13卷 208-221页

作者： nicole oneyear Shauna Hallmark Amrita Goswamy Raju Thapa Guillermo Basulto-Elias Institute for Transportation Iowa State University Ames USA

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.

关键词： Naturalistic Driving Study Data Intersection Safety Rural Stopping Behavior

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