Commercial Motor Vehicle Driver Restart Study [Research Brief]

NHTSA · 2017 · ROSA P / United States. Department of Transportation. Federal Motor Carrier Safety Administration

archive: archived pipeline: cataloged verified

Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)

Summary

This research brief summarizes the Commercial Motor Vehicle Driver Restart Study, a naturalistic field study sponsored by the Federal Motor Carrier Safety Administration (FMCSA). The study was mandated by the Consolidated and Further Continuing Appropriations Act of 2015 to evaluate the operational, safety, health, and fatigue impacts of two specific Hours-of-Service (HOS) provisions: the requirement for at least two nighttime periods (1 a.m. to 5 a.m.) during a 34-hour restart break, and the limitation of using this restart once every 168 hours. These provisions were suspended in December 2014, prompting the investigation into their effects on commercial motor vehicle (CMV) drivers. The study employed a naturalistic design where 235 drivers (mean age 45, predominantly male) worked their normal schedules over a period of up to five months. Data were collected using electronic logging devices, onboard monitoring systems with video recorders, wrist-worn actigraphy devices, and smartphone applications. The smartphone apps facilitated Brief Psychomotor Vigilance Tests (PVT-B), subjective ratings of fatigue and stress, and sleep diaries. The research compared outcomes among drivers using a 1-night restart versus a 2-night (or more) restart, as well as those taking restarts less than 168 hours apart versus those taking them at least 168 hours apart. The findings indicated no meaningful differences in key outcome metrics between the various restart provisions. Drivers using 1-night and 2-night restarts exhibited similar average daily work hours (10.11–10.22 hours), sleep durations (6.47–6.57 hours during duty periods; 8.82–8.85 hours during restart periods), rates of safety-critical events (0.34–0.37 per 100 instrumented hours), PVT response speeds, and subjective stress scores. Similarly, drivers with restart intervals shorter or longer than 168 hours showed comparable results across all domains. Statistically significant findings were limited to the observation that drivers slept significantly more during restart periods than during duty cycles and reported significantly lower stress levels during restart periods compared to duty cycles. The study concludes that while the specific manner in which the restart provisions were utilized did not significantly alter safety, fatigue, or operational outcomes, the 34-hour restart period itself is beneficial. It provides drivers with necessary sleep time and quality to recover from acute or cumulative fatigue and reduces subjective stress. The results underscore the importance of off-duty time for recovering from sleep debt accrued during duty cycles, affirming the value of the restart period despite the negligible differences between the specific regulatory variations tested.

Key finding

Drivers using a 1-night versus 2-night restart showed no meaningful differences in work hours (10.11 to 10.22 per day), sleep, safety-critical events (0.34 to 0.37 per 100 hours), vigilance, or stress.

Methodology

naturalistic

Sample size: 235

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 (7 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.

• truck driver fatigue
• hours of service
• shift work driving
• time on task
• sleep deprivation

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: physiological data