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J Safety Res ; 54: 5-15, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26403901

ABSTRACT

INTRODUCTION: The Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS) data were used to evaluate gap acceptance behavior of drivers at left-turn lanes with negative, zero, or positive offsets ranging from -29 ft to +6 ft. The objectives of the study were to develop guidance for the design of offset left-turn lanes used as a safety countermeasure, and to provide insight regarding the use of the NDS data to future users. METHOD: The study included 3350 gaps in opposing traffic evaluated by 145 NDS volunteer drivers and 275 non-NDS drivers at 14 two-way stop-controlled intersections and 44 signalized opposing left-turn pairs. Logistic regression was used to model the critical gap length for drivers as a function of offset, under conditions when their view was either blocked or not by an opposing left-turning driver. RESULTS: The analysis found that the critical gap was longer at left-turn lanes with negative offsets than at those with zero or positive offsets, and was also longer when sight distance was blocked by an opposing left-turning vehicle. Sight distance was much more likely to be restricted by an opposing left-turning vehicle at negative-offset and drivers at those intersections were less likely to accept a gap when an opposing left-turn driver was present. CONCLUSIONS: Longer gap lengths could potentially result in decreased operational efficiency of an intersection. In addition, drivers making left-turns at negative-offset left-turn lanes are, on average, more likely to leave the shortest amount of time between their turn and the arrival of the next opposing through-vehicle, which may present a potential safety concern. PRACTICAL APPLICATIONS: The findings provide guidance for highway designers considering using offset left-turn lanes as a crash countermeasure. This research also highlights the benefits and limitations of using the SHRP 2 NDS data to answer similar research questions.


Subject(s)
Accidents, Traffic/prevention & control , Automobile Driving , Environment Design , Safety , Humans , Logistic Models , Motor Vehicles , Problem Solving
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