FMCSA has been addressing crucial driver issues such as distraction for years. Until 2006, driver distraction was widely believed to be a contributing factor in as many as 30 percent of all crashes as indicated by crash databases (comprised of police accident reports, which were the primary data source for understanding pre-crash driver behavior). In 2006, a naturalistic driving study conducted with 100 light vehicles (i.e., primarily passenger automobiles) found driver distraction in 78 percent of crashes. To gather naturalistic driving data, each vehicle typically contains several video cameras (e.g., recording views of the face, over-the-shoulder, front view, rearview, right/left side view, and foot pedals) and vehicle sensors to collect data on vehicle speed, global positioning system, braking intensity, steering input, forward range to a lead vehicle, and many additional measures. These data are generally collected continuously; that is, the data collection system is started as soon as the vehicle ignition starts and continues to record until the vehicle is turned off. For this investigation into the impact of driver distraction on commercial motor vehicle (CMV) operations, data from two earlier naturalistic CMV driving studies were analyzed to produce odds ratios to determine the odds of an outcome (such as a crash) occurring as compared with normal, non-event, baseline driving. From those odds ratios, population attributable risk (PAR) percentages were calculated to consider the frequency of occurrence of each task.
Driver Distraction in Commercial Vehicle Operations. TechBrief
2009
4 pages
Report
Keine Angabe
Englisch
Transportation Safety , Road Transportation , Job Environment , Transportation & Traffic Planning , Transportation , Motor vehicle operators , Driver behavior , Distraction , Literature reviews , Data reduction , Recommendations , Data analysis , Crash risks , Inattention , Driver performance , Driver safety , Driver distraction , Commercial motor vehicles(CMV) , Eye glance analyses , Drowsy Driver Warning System , Naturalistic Truck Driving Study , Naturalistic data , Safety critical events
Driver Distraction in Commercial Vehicle Operations
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