Richard Hanowski

Dr. Richard Hanowski

orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2016 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
GCGuang Xiang Chen
Guang Xiang Chen
YFYoujia Fang
Youjia Fang
Feng GuoFeng Guo
Feng Guo
RHRichard Hanowski
Richard Hanowski

1 November 2007 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
RHRichard Hanowski
Richard Hanowski
JHJeffery Hickman
Jeffery Hickman
MFMaria C. Fumero
Maria C. Fumero
RORebecca L. Olson
Rebecca L. Olson
TDThomas A. Dingus
Thomas A. Dingus

1 March 2003 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
RHRichard Hanowski
Richard Hanowski
WWWalter W Wierwille
Walter W Wierwille
TDThomas A Dingus
Thomas A Dingus

1 May 2019 in Accident Analysis & Prevention
Verified
Journal Article
Open access
HSHal S. Stern
Hal S. Stern
DBDaniel Blower
Daniel Blower
MCMichael L. Cohen
Michael L. Cohen
CCCharles A. Czeisler
Charles A. Czeisler
DDDavid F. Dinges
David F. Dinges
DWDavid Wegman
David Wegman
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.

JMJ.Erin Mabry
J.Erin Mabry
MCMatthew Camden
Matthew Camden
AMAndrew Miller
Andrew Miller
Abhijit SarkarAbhijit Sarkar
Abhijit Sarkar
AMAditi Manke
Aditi Manke
RHRichard Hanowski
Richard Hanowski
Fatigue can be a significant problem for commercial motor vehicle (CMV) drivers. The lifestyle of a long-haul CMV driver may include long and irregular work hours, inconsistent sleep schedules, poor eating and exercise habits, and mental and physical stress, all contributors to fatigue. Shiftwork is associated with lacking, restricted, and poor-quality sleep and variations in circadian rhythms, all shown to negatively affect driving performance through impaired in judgment and coordination, longer reaction times, and cognitive impairment. Overweight and obesity may be as high as 90% in CMV drivers, and are associated with prevalent comorbidities, including obstructive sleep apnea, hypertension, and cardiovascular and metabolic disorders. As cognitive and motor processing declines with fatigue, driver performance decreases, and the risk of errors, near crashes, and crashes increases. Tools and assessments to determine and quantify the nature, severity, and impact of fatigue and sleep disorders across a variety of environments and populations have been developed and should be critically examined before being employed with CMV drivers. Strategies to mitigate fatigue in CMV operations include addressing the numerous personal, health, and work factors contributing to fatigue and sleepiness. Further research is needed across these areas to better understand implications for roadway safety.

1 January 2007 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
RHRichard Hanowski
Richard Hanowski
JHJeffery S. Hickman
Jeffery S. Hickman
WWWalter W. Wierwille
Walter W. Wierwille
AKAysha Keisler
Aysha Keisler