Asleep at the Wheel–the Road to Addressing Drowsy Driving

Higgins, J. Stephen; Michael, Jeff; Austin, Rory; Akerstedt, Torbjorn; Van Dongen, Hans P.A.; Watson, Nathaniel; Czeisler, Charles; Pack, Allan I.; Rosekind, Mark R. · 2017 · ROSA P / Oxford University Press

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Summary

This article outlines a strategic framework for addressing drowsy driving, a significant public health and safety issue that contributes to thousands of deaths and injuries annually. The authors, representing the National Highway Traffic Safety Administration (NHTSA) and various sleep science and traffic safety organizations, argue that while drowsy driving is a controllable behavior, effective strategies for the general public have been lacking. The paper synthesizes conclusions from a 2015 NHTSA forum, "Asleep at the Wheel," which convened stakeholders to establish a coordinated national effort involving traffic safety experts, sleep scientists, and policymakers. The authors highlight that drowsy driving crashes are severely underreported due to difficulties in determining drowsiness from police reports and a lack of objective measurement tools. While official data cites approximately 846 fatalities in 2014, statistical modeling suggests the true toll may exceed 6,000 deaths and result in an estimated $109 billion in societal costs annually. Risk factors include sleep restriction, shift work, adolescent circadian rhythms, and medical conditions like obstructive sleep apnea. The paper notes that while commercial drivers are regulated, the general driving public lacks comparable safeguards, and societal norms often conflict with the need for sufficient sleep. To address these challenges, the paper proposes a multi-faceted approach centered on five priority areas. First, it calls for improved crash investigation and reporting, including better training for investigators and the development of biomarkers for sleep deprivation to enable roadside testing similar to alcohol breathalyzers. Second, it emphasizes public awareness through broad health campaigns, victim advocacy, and the inclusion of drowsy driving risks in driver’s education and manuals. Third, it advocates for vehicle technology advancements, specifically the validation and deployment of drowsy driving warning systems and collision avoidance technologies, alongside consumer education on their use. Fourth, it recommends policy changes, such as developing model state laws to prosecute negligent drowsy driving and promoting corporate fatigue management programs. Finally, it suggests infrastructure improvements, such as expanding highway rest areas and deploying rumble strips to alert drifting drivers. The significance of this work lies in its call for a unified, interdisciplinary strategy to treat drowsy driving with the same seriousness as drunk driving. By bridging the gap between sleep science and traffic safety, the authors aim to shift societal norms, improve data accuracy, and implement comprehensive countermeasures. The proposed actions range from immediate educational interventions to long-term technological and legislative developments, aiming to reduce the prevalence of drowsy driving and mitigate its severe economic and human costs.

Key finding

Drowsy driving crashes are substantially underreported in official statistics, with estimates suggesting that up to 16.5% of fatal crashes involve a drowsy driver, leading to an estimated 6,000 annual deaths and $109 billion in societal costs.

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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).

StageOutcomeToolModelPromptAttemptsCompleted
discover success rosap 2 2026-05-23
archive success 1 2026-05-23
extract success cached 2 2026-06-10
clean success 1 2026-06-01
chunk success 1 2026-06-01
embed success 1 2026-06-02
enrich success 1 2026-05-23
promote success 1 2026-05-23
summarize success llm qwen3.6-27b-prismaquant summ-v5 3 2026-06-10
tag success vector_similarity 19 2026-06-11
verify success 2 2026-06-10

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

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