Based in Madison, Wisconsin, CTC & Associates provides technical communications services for the transportation sector, and together with the Minnesota Department of Transportation (MnDOT), they put together a report on how to monitor driver fatigue:
to serve as a synthesis of pertinent completed research to be used for further study and evaluation by MnDOT. This [Transport Research Synthesis (TRS)] does not represent the conclusions of either CTC & Associates or MnDOT. (MnDOT, 2015)
The following (apart from ESS - see below) are some of the studies presented in the MnDOT report.
In-vehicle Technologies
Balkin, et al. (2011) talks about technologies which can detect or predict driver fatigue.
Technologies that objectively detect or predict operator fatigue may be used to effectively complement or even supplant organizational or regulatory approaches. Over the past decade and a half, there have been considerable advances in relevant technologies, including onboard devices that monitor drivers’ state or level of performance as well as devices that predict fatigue in advance of a work cycle or trip.
Barr, Popkin and Howarth (2009) also reviews and discusses unobtrusive, in-vehicle, real-time drowsy driver detection and fatigue monitoring/alerting systems.
The study focuses on recent developments in two areas:
- Mathematical models that predict operator alertness and performance at different times. Factors
involved in the assessment include the amount of sleep obtained or missed, circadian factors (the 24-
hour cycle of physical, mental and behavioral changes) and workload.
- Vehicle-based monitoring technologies that assess behavioral characteristics of the driver such as eye
gaze, eye closure, head position and movement, and heart rate.
Roadside and other Out-of-vehicle technologies
Fitness for Duty
There is the Karolinska Sleepiness Scale [KSS] (Åkerstedt & Gillberg, 1990; Kaida, et al., 2006) and there is the Epworth Sleepiness Scale [ESS] (Johns, 1991). Both are self-report scales, frequently used in studies measuring subjective sleepiness, that measure the individual’s drowsiness. The KSS is a 9-point verbally anchored scale going from ‘extremely alert’ to ‘extremely sleepy–fighting sleep’, whereas the ESS uses a 4-point scale from never doze to high chance of dozing.
The Epworth Sleepiness Scale (ESS) (named after The Epworth Sleep centre in Melbourne, Australia) is used by doctors here in the UK to point toward the possibility of sleep disorders such as Sleep Apnoea. You can see an example PDF of the questionnaire at the Warrington and Halton NHS Hospitals website. It is a self-evaluation questionnaire devised to determine general sleepiness observed by the individual based on usual chances of dozing off or falling asleep while engaged in eight different activities.
Not wishing to add any validity to the system, I thought I would mention that Optalert talks about a testing system they developed themselves and are promoting, called the Johns Drowsiness Scale (JDS). It was developed by Optalert’s Founding Director, and developer of ESS, Dr Murray Johns, and comparing it to ESS, and Blood Alcohol Concentration Readings, they say that
With 30 Per Cent Of Road Fatalities Attributed To Drowsy Driving, At Optalert We Believe The Johns Drowsiness Scale (JDS™) Will, In The Near Future, Become As Important As Blood Alcohol Concentration (BAC) Readings. (Source: JDS vs BAC - Optalert)
Whilst assessing the use of a simple balance task for assessing fitness for duty, Sargent et al. (2012) states:
results indicate that postural balance may be a viable tool for assessing fatigue associated with time of day, but may not be useful for assessing fatigue associated with extended hours of wake.
Roadside Testing
A pilot study was conducted (Forsman, et al., 2014) and it states that the method put together for the pilot...
further developed, may provide a drowsiness test for roadside surveillance.
Further Reading
MnDOT. (2015) Monitoring Motor Vehicle Driver Fatigue
Retrievable form http://dotapp7.dot.state.mn.us/projectPages/pages/projectDetails.jsf?id=35917&type=DOCUMENT
Plus Chapters 9 & 10 of:
National Academies of Sciences, Engineering and Medicine. (2016). Commercial Motor Vehicle Driver Fatigue, Long-Term Health, and Highway Safety. Washington (DC): National Academies Press
DOI: 10.17226/21921 NBK: 384966 [Free PDF]
References
Åkerstedt, T., & Gillberg, M. (1990). Subjective and objective sleepiness in the active individual. International Journal of Neuroscience, 52(1-2), 29-37.
DOI: 10.3109/00207459008994241 PMID: 2265922
Balkin, T. J., Horrey, W. J., Graeber, R. C., Czeisler, C. A., & Dinges, D. F. (2011). The challenges and opportunities of technological approaches to fatigue management. Accident Analysis & Prevention, 43(2), 565-572.
DOI: 10.1016/j.aap.2009.12.006
Barr, L., Popkin, S., & Howarth, H. (2009). An evaluation of emerging driver fatigue detection measures and technologies (No. FMCSA-RRR-09-005). United States: Federal Motor Carrier Safety Administration.
Retreivable at https://rosap.ntl.bts.gov/view/dot/34394
Johns, M. W. (1991). A New Method for Measuring Daytime Sleepiness: The Epworth Sleepiness Scale. Sleep, 14(6), 540-545.
DOI: 10.1093/sleep/14.6.540
Forsman, P., Pyykkö, I., Toppila, E., & Hæggström, E. (2014). Feasibility of force platform based roadside drowsiness screening–A pilot study. Accident Analysis & Prevention, 62, 186-190.
DOI: 10.1016/j.aap.2013.09.015
Kaida, K., Takahashi, M., Åkerstedt, T., Nakata, A., Otsuka, Y., Haratani, T., & Fukasawa, K. (2006). Validation of the Karolinska sleepiness scale against performance and EEG variables. Clinical Neurophysiology, 117(7), 1574-1581.
DOI: 10.1016/j.clinph.2006.03.011
MnDOT. (2015) Monitoring Motor Vehicle Driver Fatigue
Retrievable form http://dotapp7.dot.state.mn.us/projectPages/pages/projectDetails.jsf?id=35917&type=DOCUMENT
TRSs are also searchable at http://dotapp7.dot.state.mn.us/projectPages/pages/homepage.jsf
Sargent, C., Darwent, D., Ferguson, S. A., & Roach, G. D. (2012). Can a simple balance task be used to assess fitness for duty?. Accident Analysis & Prevention, 45, 74-79.
DOI: 10.1016/j.aap.2011.09.030