The purpose of this study was to investigate the impact of driver distraction in commercial motor vehicle (CMV) operations. To accomplish this, data from two large-scale naturalistic studies were combined creating a data set that included over 200 CMV drivers and seven trucking fleets operating at 16 locations, accounting for approximately 3 million miles of continuous driving. Naturalistic data collection involves the instrumentation of in-service trucks with kinematic sensors, video cameras, and other equipment. CMV drivers use these equipped trucks while they operate their normal revenue-producing runs. A total of 4,452 safety-critical events (i.e., crashes, near-crashes, crash-relevant conflicts, and unintended lane deviations) were identified in the data set, along with 19,888 baseline (non-event) epochs. Key findings were that highly complex tasks, including those involving the use of technology while driving, lead to a significant increase in risk. Eye glance analyses were also conducted to examine driver eye location while performing tasks while driving. Tasks associated with high odds ratios (increased risk) were also associated with high eyes off forward road times. Based on the results of the analyses, a number of recommendations are presented that may help address the issue of driver distraction in CMV operations.
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