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Journal Article

Citation

Harland KK, Carney C, McGehee D. Traffic Injury Prev. 2016; 17(5): 465-471.

Affiliation

Human Factors and Vehicle Safety Research Division, Public Policy Center, University of Iowa , Iowa City , IA.

Copyright

(Copyright © 2016, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2015.1118655

PMID

26760293

Abstract

OBJECTIVE To estimate the prevalence and odds of fleet driver errors and potentially distracting behaviors just prior to rear-end versus angle crashes.

METHODS Analysis of naturalistic driving videos among fleet services drivers for errors and potentially distracting behaviors occurring in the six seconds before crash impact. Categorical variables were examined using the Pearson Chi-square test and continuous variables, such as eyes-off-road time, were compared using the Student's t-test. Multivariable logistic regression was used to estimate the odds of a driver error or potentially distracting behavior being present in the seconds before rear-end versus angle crashes.

RESULTS Of the 229 crashes analyzed, 101 (44%) were rear-end and 128 (56%) were angle crashes. Driver age, gender and presence of passengers did not differ significantly by crash type. Over 95% of rear-end crashes involved inadequate surveillance compared to only 52% of angle crashes (<0.0001). Almost 65% of rear-end crashes involved a potentially distracting driver behavior while less than 40% of angle crashes involved these behaviors (p<0.01). On average, drivers spent 4.4 seconds with their eyes off the road while operating or manipulating their cell phone. Drivers in rear-end crashes were at 3.06 (95% CI: 1.73-5.44) times adjusted higher odds of being potentially distracted than those in angle crashes.

CONCLUSIONS Fleet driver driving errors and potentially distracting behaviors are frequent. This analysis provides data to inform safe driving interventions for fleet services drivers. Further research is needed in effective interventions to reduce the likelihood of driver distracting behaviors and errors which may potentially reducing crashes.


Language: en

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