Driver Distraction in Commercial Vehicle Operations

Olson, Rebecca L.; Hanowski, Richard J.; Hickman, Jeffrey S.; Bocanegra, Joseph; Virginia Tech Transportation Institute: Center for Truck and Bus Safety · 2010 · OpenAlex-citations

DOI: 10.21949/1502647

archive: archived pipeline: cataloged verified

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Summary

This study, conducted by the Virginia Tech Transportation Institute for the Federal Motor Carrier Safety Administration, investigates the impact of driver distraction on commercial motor vehicle (CMV) safety. The research aims to characterize driver inattention during safety-critical events compared to baseline driving and to determine the relative risk associated with distracted driving. The study utilizes naturalistic driving data to provide empirical evidence on how non-driving-related tasks contribute to crashes, near-crashes, and other critical incidents in commercial trucking operations. The methodology combines data from two earlier naturalistic studies: the Drowsy Driver Warning System Field Operational Test and the Naturalistic Truck Driving Study. The final dataset includes 203 CMV drivers and 55 trucks from seven fleets operating across 16 locations. Researchers identified 4,452 safety-critical events (including crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations) and 19,888 baseline epochs representing uneventful, routine driving. Data analysis involved calculating odds ratios to assess the likelihood of safety-critical events while engaging in specific tasks and estimating population attributable risk. Additionally, eye glance analyses were performed to examine the duration and frequency of drivers’ eyes being off the forward roadway while performing various tasks, categorized by manual and visual complexity. The results indicate that drivers were engaged in non-driving-related tasks in 71% of crashes, 46% of near-crashes, and 60% of all safety-critical events. Performing highly complex tasks while driving significantly increased the risk of involvement in safety-critical events. Eye glance analyses revealed a strong correlation between high odds ratios and increased time with eyes off the forward roadway. Specifically, tasks associated with higher risk, such as texting, using dispatching devices, and reading, required longer durations of visual attention away from the road. The study also examined how environmental conditions, such as lighting, weather, and traffic density, interacted with task engagement, finding that distraction risks persisted across various conditions but were exacerbated by complex visual demands. The significance of these findings lies in the clear link between visual distraction and CMV safety risks. The study concludes that tasks drawing drivers’ visual attention away from the forward roadway should be minimized or avoided to reduce crash risk. Based on the evidence that complex tertiary tasks pose the greatest danger, the report offers recommendations for addressing driver distraction in commercial operations. These findings provide a data-driven foundation for regulatory policies and safety interventions aimed at reducing inattention-related crashes in the trucking industry.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-25; verification: verified.

Topics

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• visual
• external distraction
• visual manual
• distraction detection algorithms
• temporal
• manual

Information type

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• Empirical Findings: behavioral performance data, observational prevalence, crash risk outcomes