Distraction in Commercial Trucks and Buses: Assessing Prevalence and Risk in Conjunction with Crashes and Near-Crashes [Tech Brief]

NHTSA · 2010 · ROSA P / United States. Federal Motor Carrier Safety Administration

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Summary

This study, conducted by the Federal Motor Carrier Safety Administration (FMCSA) and Virginia Tech Transportation Institute, investigates the prevalence and risk of distracted driving among commercial truck and bus drivers. The research aims to support the strategic objective of producing safer drivers by documenting how specific tertiary tasks—actions that divert attention from driving—affect the likelihood of involvement in safety-critical events. The study utilizes naturalistic driving data to assess associations between driver behaviors and crashes or near-crashes, providing evidence to inform safety policies and vehicle interface design. The analysis relied on kinematic and driver behavior data provided by DriveCam®, an onboard safety monitoring system vendor, covering a one-year period. The primary dataset (Data Set B) included 13,306 vehicles from 183 fleets, capturing 1,085 crashes, 8,375 near-crashes, 30,661 crash-relevant conflicts, and 211,171 baseline events. Data were recorded only when kinematic thresholds were exceeded (≥0.5 g), serving as triggers for both safety-critical and non-safety events. The study calculated odds ratios to determine the association between specific tertiary tasks and safety-critical events, while also evaluating the impact of fleet cell phone policies and state laws on driver behavior. Key findings indicate that tasks requiring high visual attention significantly increase crash risk. Texting, emailing, or accessing the internet while driving was associated with an extremely high odds ratio of 163.59, with 90 of 93 instances resulting in safety-critical events. Other high-risk tasks included dialing a cell phone (odds ratio 3.51), reaching for a cell phone (3.74), and reaching for a headset (3.38). In contrast, talking or listening on a hands-free cell phone showed a protective effect (odds ratio 0.65), and hand-held talking showed no significant increase in risk. Overall, any cell phone usage increased the odds of a safety-critical event by 1.14 times. Regarding policy effectiveness, the presence of a fleet cell phone policy reduced the odds of cell phone use by 17% (odds ratio 0.83), whereas state cell phone laws had no significant impact on usage rates (odds ratio 0.97). The study concludes that visual distraction is the primary driver of increased risk in commercial vehicle operations. While conversational tasks alone do not significantly increase risk, the manual and visual demands of initiating calls (reaching and dialing) do. The authors note limitations, including potential bias toward safer behavior due to the monitoring system’s feedback nature and media attention during data collection. These findings suggest that safety interventions should target high-visual-demand tasks and that fleet policies are more effective than state laws in reducing cell phone usage among commercial drivers.

Key finding

Texting, emailing, or accessing the internet while driving was associated with an odds ratio of 163.59 for involvement in a safety-critical event, significantly higher than other distracted driving behaviors.

Methodology

naturalistic

Sample size: 13306

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

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

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• distraction detection algorithms
• visual
• naturalistic crash near crash
• mobile phones
• external distraction
• distraction laws

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: observational prevalence, crash risk outcomes
• Methodological Resource: dataset resource