Driver Distraction in Commercial Vehicle Operations

Olson, R.L.; Hanowski, R.J.; Hickman, J.S.; Bocanegra, Joseph L · 2009 · ROSA P / United States. Department of Transportation. Federal Motor Carrier Safety Administration

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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 safety in commercial motor vehicle (CMV) operations. 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 was motivated by the need to understand how non-driving-related tasks contribute to crashes and near-crashes in heavy vehicle operations. The researchers utilized naturalistic driving data from two earlier studies: the Drowsy Driver Warning System Field Operational Test and the Naturalistic Truck Driving Study. The combined dataset included 203 CMV drivers and 55 trucks from seven fleets operating across 16 locations. The analysis focused on 4,452 safety-critical events (crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations) and 19,888 baseline epochs representing routine, uneventful driving. Data reduction involved identifying event triggers, validating events, and coding driver tasks and eye glance locations. Statistical analyses included odds ratio calculations to assess the likelihood of safety-critical events while engaging in specific tasks and population attributable risk estimates to determine the proportion of events attributable to distraction. Key findings 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 significantly increased the risk of involvement in safety-critical events. Eye glance analyses revealed a strong correlation between high-risk tasks and prolonged periods with eyes off the forward roadway. Specifically, tasks associated with high odds ratios also involved longer durations and greater numbers of glances away from the road. The study further examined how environmental conditions, such as lighting, weather, and traffic density, interacted with task engagement to influence risk. For instance, the risk associated with certain tasks varied depending on whether the driver was in daylight or nighttime conditions, or in high versus low traffic density. The significance of this research lies in its empirical evidence linking visual distraction to increased crash risk in commercial driving. The findings suggest that tasks drawing visual attention away from the forward roadway should be minimized or avoided to enhance safety. The study provides specific recommendations for addressing driver distraction in CMV operations, emphasizing the need to reduce the frequency and complexity of non-driving tasks. By quantifying the risk associated with specific behaviors and environmental contexts, the report offers a data-driven basis for regulatory and operational interventions aimed at reducing crashes involving commercial vehicles. The study highlights the importance of naturalistic data in understanding real-world driving behaviors and their safety implications.

Key finding

Drivers were engaged in non-driving related tasks in 71 percent of crashes, 46 percent of near-crashes, and 60 percent of all safety-critical events, with highly complex tasks significantly increasing risk.

Methodology

naturalistic

Sample size: 203

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

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