Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health

Hal S. Stern, Daniel Blower, Michael L. Cohen, Charles A. Czeisler, David F. Dinges, Joel B. Greenhouse, Feng Guo, Richard J. Hanowski, Natalie P. Hartenbaum, Gerald P. Krueger, Melissa M. Mallis, Richard F. Pain, Matthew Rizzo, Esha Sinha, Dylan S. Small, Elizabeth A. Stuart, David H. Wegman

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health.

Original languageEnglish (US)
Pages (from-to)37-42
Number of pages6
JournalAccident Analysis and Prevention
Volume126
DOIs
StatePublished - May 2019

Fingerprint

Motor Vehicles
fatigue
motor vehicle
Fatigue
driver
Health
Fatigue of materials
Safety
health
Statistical methods
statistical method
Information Storage and Retrieval
Medicine
Academy of Sciences
medicine
engineering
methodology

Keywords

  • Causal inference
  • Driver performance
  • Longitudinal studies
  • Observational studies
  • Obstructive sleep apnea

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health
  • Law

Cite this

Stern, H. S., Blower, D., Cohen, M. L., Czeisler, C. A., Dinges, D. F., Greenhouse, J. B., ... Wegman, D. H. (2019). Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health. Accident Analysis and Prevention, 126, 37-42. https://doi.org/10.1016/j.aap.2018.02.021

Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health. / Stern, Hal S.; Blower, Daniel; Cohen, Michael L.; Czeisler, Charles A.; Dinges, David F.; Greenhouse, Joel B.; Guo, Feng; Hanowski, Richard J.; Hartenbaum, Natalie P.; Krueger, Gerald P.; Mallis, Melissa M.; Pain, Richard F.; Rizzo, Matthew; Sinha, Esha; Small, Dylan S.; Stuart, Elizabeth A.; Wegman, David H.

In: Accident Analysis and Prevention, Vol. 126, 05.2019, p. 37-42.

Research output: Contribution to journalArticle

Stern, HS, Blower, D, Cohen, ML, Czeisler, CA, Dinges, DF, Greenhouse, JB, Guo, F, Hanowski, RJ, Hartenbaum, NP, Krueger, GP, Mallis, MM, Pain, RF, Rizzo, M, Sinha, E, Small, DS, Stuart, EA & Wegman, DH 2019, 'Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health', Accident Analysis and Prevention, vol. 126, pp. 37-42. https://doi.org/10.1016/j.aap.2018.02.021
Stern, Hal S. ; Blower, Daniel ; Cohen, Michael L. ; Czeisler, Charles A. ; Dinges, David F. ; Greenhouse, Joel B. ; Guo, Feng ; Hanowski, Richard J. ; Hartenbaum, Natalie P. ; Krueger, Gerald P. ; Mallis, Melissa M. ; Pain, Richard F. ; Rizzo, Matthew ; Sinha, Esha ; Small, Dylan S. ; Stuart, Elizabeth A. ; Wegman, David H. / Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health. In: Accident Analysis and Prevention. 2019 ; Vol. 126. pp. 37-42.
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