To reduce traffic congestion in the United States, roadway maintenance and construction operations are widely performed during nighttime hours. This makes visibility a critical issue as workers need to be visible to oncoming traffic and heavy equipment operators in order to ensure their safety. A variety of high-visibility safety garments are available to increase the visibility of workers at night. The study presented in this paper assesses some of these garments from the perspective of drivers. The approach adopted includes the design of a field test setup in which eight safety garment assemblies were displayed in a replicated maintenance work zone. A video was created for each safety garment assembly being worn by workers to capture the approaching view of a driver entering the work zone. The videos were shown to drivers, who evaluated the visibility of the garments in pairwise comparisons. Two random effects binary probit models were estimated. One model was used to understand the characteristics that would make it more likely that the subject could detect a difference between a high-visibility vest used by the Indiana Department of Transportation workers and a competing assembly. The amount of background and retroreflective material, the driver’s age, and the speed at they which they traveled through the work zone were found to be significant in this model. A second model was a conditional one: given that a difference in garments could be detected, was the competing garment assembly more or less visible than the current safety garment used by the Indiana Department of Transportation? In this case, the mean and variance of the retroreflective material of the garment and the lighting in the work environment were found to be significant. (Author/publisher)
Abstract