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J Safety Res ; 74: 45-53, 2020 09.
Article in English | MEDLINE | ID: mdl-32951795

ABSTRACT

INTRODUCTION: The present study discusses roles, characteristics, and safety assessment of a drowsy driving advisory (DDA) system, implemented on rural interstates of Alabama. The DDA system is an engineering countermeasure designed to reduce the likelihood of drowsy driving crashes. It consists of a series of roadside signs with warning and advisory messages for drowsy drivers. The DDA system was implemented upstream of rural rest areas based on a comprehensive crash analysis. METHOD: A post-implementation study was conducted three years after the DDA system implementation to assess its safety effects. An empirical bayes (EB) method along with predictive methods of the Highway Safety Manual was used in the safety assessment. To overcome the underreported issue of drowsy driving crashes in the crash analysis, the present study used a concept called, expanded definition of drowsy driving (EDD) crashes. RESULT: The analysis found that the DDA system could reduce total and EDD crashes by 64% and 49%, respectively. It is important to note that such huge crash reduction effects are due to a combined effect of both rest areas and the DDA system, not because of a single treatment. The safety effect of a rest area itself, without considering the effect of the DDA system, was also investigated. Results show that total and EDD crashes would increase about 12-45% and 5-33%, respectively if there is no presence of a rest area. CONCLUSION: Our findings conclude that the DDA system could significantly reduce both total and drowsy driving crashes when it cooperates with a rest area facility. Practical Application: The findings also provide the guidance of using the DDA system on high-speed roads as a safety countermeasure of drowsy driving crashes. Readers can find details of the DDA system used in this study with its layout, dimension, and roadside safety messages.


Subject(s)
Distracted Driving/prevention & control , Safety/statistics & numerical data , Alabama , Humans , Wakefulness
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