Abstract
Driver distraction is a recognized cause of traffic accidents. Although the well-known guidelines for measuring distraction of secondary in-car tasks were published by the United States National Highway Traffic Safety Administration (NHTSA) in 2013, studies have raised concerns on the accuracy of the method defined in the guidelines, namely criticizing them for basing the diversity of the driver sample on driver age, and for inconsistent between-group results. In fact, it was recently discovered that the NHTSA driving simulator test is susceptible to rather fortuitous results when the participant sample is randomized. This suggests that the results of said test are highly dependent on the selected participants, rather than on the phenomenon being studied, for example, the effects of touch screen size on driver distraction. As an attempt to refine the current guidelines, we set out to study whether a previously proposed new testing method is as susceptible to the effects of participant randomization as the NHTSA method. This new testing method differs from the NHTSA method by two major accounts. First, the new method considers occlusion distance (i.e., how far a driver can drive with their vision covered) rather than age, and second, the new method considers driving in a more complex, and arguably, a more realistic environment than proposed in the NHTSA guidelines. Our results imply that the new method is less susceptible to sample randomization, and that occlusion distance appears a more robust criterion for driver sampling than merely driver age. Our results are applicable in further developing driver distraction guidelines and provide empirical evidence on the effect of individual differences in drivers’ glancing behavior.
Highlights
We set out to investigate if by manipulating driver samples we can affect distraction testing results when using a new, previously reported distraction potential testing method that validates the driver sample based on drivers’ occlusion distances. This validation ensures that the driver sample contains drivers with different glancing behaviors measured with occlusion distance
Our results indicate that these results obtained with this new method are not affected by manipulating driver samples when the sample includes all kinds of drivers – from those who are able to drive longer occlusion distances to those who are able to drive shorter occlusion distances
This indicates that the method tested in this study might account for individual driver differences more accurately than, for example, tests that utilize the National Highway Traffic Safety Administration (NHTSA) guidelines, which are shown to be susceptible to participant sample manipulation
Summary
Driver inattention – which is often caused by digital devices used during driving – is a universally recognized phenomenon that is connected to accidents and near-accidents in traffic (e.g., Bayer & Campbell, 2012; Caird et al, 2014; Choudhary & Velaga, 2017; Gauld et al, 2017; Guo et al, 2010; He et al, 2015; Oviedo-Trespalacios et al, 2016; Rumschlag et al, 2015; Tivesten & Dozza, 2015). Regan et al (2011) have proposed a taxonomy regarding driver inattention. Driver distraction is a form of driver inattention, and being distracted requires some competing activity while driving. The taxonomy suggests that a driver can be inattentive while not being distracted, but not be distracted without being inattentive. This categorization (Regan et al, 2011) of driver distraction being a subcategory of driver inattention is adopted here
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More From: Transportation Research Part F: Traffic Psychology and Behaviour
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