Which Five Factors Affects Driver Fatigue & Alertness The Least?

TASA ID: 9075

Here’s a quiz with just one question:  Which of the five factors affects driver fatigue (i.e., drowsiness) and alertness the least?  

A. Individual differences in susceptibility to drowsiness
B. Amount of prior sleep
C. Time-of-day
D. Prior continuous time awake
E. Prior continuous time driving

Before giving the answer, a definition and a disclaimer; the word “fatigue” here means drowsiness and falling asleep-at-the-wheel.  “Fatigue” is used almost universally by police, transportation officials, and safety researchers to mean sleepiness.  As used, it is not physical tiredness from exertion.  In fact, physical exertion tends to wake you up unless it is extreme.  

A needed disclaimer is that all of the five factors listed can and do affect fatigue and alertness.  But the effects of one of them are greatly exaggerated, I feel.  This exaggeration leads to the effects of the other four factors being underappreciated or even ignored.  Misunderstanding the sources of driver fatigue and asleep-at-the-wheel crashes leads people to make wrong decisions on how best to stay alert.  In the area of commercial truck and bus driving, it’s led the federal government to overemphasize prescriptive regulations while not doing enough to get to the real culprits.

My answer is (E.), prior continuous time driving.  It’s the least important of the five driving alertness factors listed.

Hours-of-driving is a type of “time-on-task,” one of the most-studied factors in human performance.  If you repeatedly test your reaction time following a randomly generated signal, your performance will decline quickly starting within 10 minutes or so.  Ever play fast-paced decision making games like speed chess?  That’s another example of where your performance will usually decline rather rapidly.  Yet, driving a motor vehicle is not a high-demand mental activity like these two examples.  Driving is mostly a low-to medium-paced psychomotor and alertness task.

Before talking more about continuous time driving, let’s talk about why the other four factors are so important.  In doing so, I will take the opportunity to acknowledge and celebrate the 25th anniversary of the 1996 U.S. DOT Driver Fatigue and Alertness Study (Wylie et al., 1996).  It was the granddaddy of instrumented vehicle studies of driver performance and behavior.  Eighty (80) U.S. and Canadian commercial, tractor-semitrailer drivers drove real, revenue-producing long-haul trips.  Miniature in-cab cameras looked at drivers’ eyes and faces, and vehicle onboard sensors measured lane-keeping and other measures of driver performance.  Drivers took reaction time and sensory motor skill tests at scheduled testing breaks.  Several major DFAS findings will be cited below.  
 

Individual differences in susceptibility
 

DFAS video recordings captured driver drowsiness episodes from eyelid drooping and facial expressions.  Eleven (11) of the 80 drivers (14%) had 54% of all the drowsy episodes recorded.  That’s a drowsiness odds ratio of 7.4 between the worst 11 drivers and the other 69.  How drowsy was the very drowsiest driver of the 80?  He had more drowsy incidents than the most alert 49 drivers combined!  Other similar studies consistently corroborate this skewed distribution of driver alertness.  If you operate a fleet, most of your asleep-at-the-wheel risk resides in about 15% of your drivers.

Susceptibility to drowsiness seems to be a long-term human trait, with repeatable individual differences.  In one laboratory study (Dinges et al., 1998), 14 healthy adult males were deprived of sleep for 42 hours.  Every two hours, they were given alertness tests.  Attentional lapses (delayed responses of >1/2 second) were the best indicators of fatigue.  Some subjects were “high lapsers;” that is, highly susceptible to attentional lapses.  These subjects had the majority of all the lapses observed.  They were almost as vulnerable to lapses during the first half of the deprivation time course as the “low lapsers” were during the second half.

When the same subjects were brought back six months later for a repeat of the test, each subject matched his/her previous performance almost identically.  The authors described subjects’ distinctive alertness deterioration patterns as being like “fingerprints.”

I know about individual sleep differences from my own life.  I take a nap almost every day, and can easily sleep in a moving vehicle.  My wife has never taken a nap in our 46+ years together.  On auto trips she drives while I sleep.  Perfect relationship!

The above studies primarily involved healthy subjects.  In addition to normal variations, medical sleep disorders like Obstructive Sleep Apnea (OSA) cause major safety risks.  Studies suggest that OSA crash involvement risks are elevated about four-fold over normal (Knipling, 2009).  If your sleeping partner tells you that you stop breathing and then gasp for breath while sleeping, take it seriously and see a doctor!
 

Amount of Prior Sleep  

You won’t be surprised to hear that prior sleep directly affects your alertness and performance.  But you might be surprised to learn how much this is true.  The AAA Safety Foundation (2018; also see Tefft, 2018) analyzed U.S. DOT crash causation data.  They found that drivers with 4-5 hours’ prior sleep had more than four times the at-fault crash rate as those who had 7+ hours of sleep.  Drivers with less than 4 hours’ sleep in the prior 24 hours were 15 times more likely to be at-fault in their crashes.  The same study looked at crash Critical Reasons (CRs); i.e., the specific driver error triggering the crash.  Asleep-at-the-wheel was identified as the CR for:

• 44% of drivers with less than 5 hours’ sleep in the prior 24 hours
• 11% of drivers with 5-6 hours’ sleep
• 2% of drivers with 6-7 hours’ sleep; and
• 0.03% of drivers with 7+ hours’ sleep. 
   

Prior sleep includes naps  

Naps are the very best countermeasure to sleepiness while driving.  In fact, the sharpest reaction times test subjects achieve are usually in the late afternoon after an earlier nap.  The ideal nap is just 20-30 minutes. 
 

Time-of-Day   

Time-of-day has a strong effect on human and animal alertness, and it’s not just because of dark-light cycles or the timing of sleep.  The brain has a 24-hour pacemaker which programs regular rises and falls in physiological arousal and alertness.  This biologically programmed daily cycle is called the circadian rhythm.

In the DFAS, time-of-day was the “strongest and most consistent factor influencing driver fatigue and alertness . . .“   High-drowsiness observed in drivers’ faces was eight times more frequent during overnight driving than during the day.  Driver performance, as measured by lateral lane deviations and performance tests, was also worse.  Your daily “alertness rollercoaster” goes up in the morning and stays high until early-afternoon, when that big lunchtime sandwich you eat likely triggers a dip.  Then alertness goes up again and doesn’t start to decline until mid-evening.  From 9:00pm or so it’s a slow ride down to the doldrums just below dawn.  In the U.S. DOT’s Large Truck Crash Causation Study (LTCCS), 62% of all truck driver asleep-at-the-wheel crash involvements occurred within just two hours, from 4:00am to 6:00am (Knipling, 2009).

Time-of-day is the one alertness factor that’s always affecting you.  Plan your daily life around it.  For me, that means trying not to schedule meetings or other mentally demanding activities in the early afternoon.  And I’m wary about the rare times when I have to get up and drive before dawn.
 

Time Awake

Do you get sleepy at about the same time every night?  What time is that, and how many hours have you typically been awake?  If you’re like most people, you get sleepy after you have been awake about 16 hours.  If you get up at 7am, you’ll get sleepy and go to bed at around 11pm.

Sixteen hours of wakefulness plus eight hours of sleep nicely equals a 24-hour day.  It’s nature’s basic program.  Given individual differences and the daily demands of life, your schedule may look more like 17 + 7 than 16 + 8.  The body’s circadian system, sleep needs, and limits on time awake drive most people toward this type of regular schedule.  If your schedule is markedly different from this, you might have a problem.

Wisely, current Hours-of-Service rules for truck drivers limit work days to 14 total hours, after which they cannot drive.  That allows a two-hour buffer before the alertness slope gets slippery at about 16 hours.  Being awake 18 hours reduces sensory-motor performance by about 6% from its daily peak.  That might not sound like much, but it is the same performance decline associated with a Blood Alcohol Content (BAC) of 0.05%, just 0.03% below the prevailing U.S. DUI threshold of 0.08% (Dawson & Reid, 1997).  In one U.S. state, Utah, the legal alcohol limit is 0.05%.
 

Time Driving

I hope I’ve convinced you that each of the above four factors strongly affects your alertness.  Each can be a principal cause for falling asleep-at-the-wheel.  It’s my opinion that the last factor listed, time driving, is less important than the other four.  My conclusion contradicts “conventional wisdom,” the simplistic belief that work causes fatigue.  Yes, work causes physical fatigue or tiredness.  But drivers don’t often crash because they are physically tired.  It’s because they are drowsy and then lapse into sleep.  The time-on-task fallacy goes back to antiquated views about work and overwork.  Federal Hours-of-Service rules for truck drivers began in the 1930s at a time when the public was rightly concerned about worker exploitation.  But we were largely ignorant back then of the real factors causing people to lose alertness while driving or operating other machinery.

Perhaps the most illuminating finding of the DFAS was related to time driving:  “Hours of driving (time-on-task) was not a strong or consistent predictor of observed fatigue.”  At the time, U.S. truck drivers could legally drive 10 hours straight, while those in Canada could drive 13 hours.  The DFAS compared them and found no consistent differences in driver alertness.

I have analyzed and compared three different types of truck crash involvements in the LTCCS.  The three truck crash involvement categories were a) not-at-fault, b) at-fault in multi-vehicle crash, and c) single-vehicle crash (almost always at-fault).  For causal analyses, not-at-fault crashes can be used as a surrogate for exposure.  The truck just happened to be there.  In at-fault multi-vehicle involvements, the truck driver did make a mistake, and it could have been due to fatigue.  Single-vehicle crashes are the biggest red flag for possible fatigue.  These crashes usually happen because drivers lose control of their vehicles, perhaps because they lose conscientiousness.

If time driving strongly affected driving performance, one would expect more hours of driving to increase the two at-fault types relative to not-at-fault involvements.  Single-vehicle crashes in particular would start off low but then increase sharply after long hours of driving.  There was no such effect.   As a function of time driving, the three incidence curves were virtually identical.

More evidence against time driving effects on alertness comes from investigations of light vehicle (e.g., car) vs. large truck crashes.  At any given time, the average car driver has been driving for well under an hour, while the typical truck driver has been driving for several hours.  Yet in car vs. large truck serious crashes, the car driver is much more likely to be asleep than the truck driver!  In the LTCCS, the car-truck fatigue ratio was 8:1 (Knipling, 2009).  Other studies have confirmed this skewed ratio (Knipling, 2015).  It's a tribute to truck drivers that they seem to maintain higher alertness levels than car drivers, even given the demands of their jobs.  When truckers do fall asleep after long hours of driving, I believe it is mostly due to other fatigue factors, including any or all of the other factors already discussed.

The subject of driver fatigue has included some of the very best and very worst research ever performed on any topic.  I’ve cited some of the best.  Among the worst are a series of U.S. DOT studies purporting to demonstrate time driving as a major factor in fatigue-related crashes.  One series of studies out of Penn State (e.g., Jovanis et al, 2011) compared truck driver logs from trips ending in a crash to those with no crash.  The studies claimed a time-on-task effect, but they did not control for the critical factors time-of-day, road type, and traffic density.  And they treated every truck crash, regardless of its characteristics, as a truck driver fatigue case.

A big study out of Virginia Tech (e.g., Blanco et al., 2011) also did not control for time-of-day, road type, or traffic density.  Worse, it had no measures of actual driver fatigue and did not even study crashes.  Instead it counted abrupt maneuvers like hard-braking and swerves.  There’s a problem with that.  Virginia Tech’s own research has shown that these types of non-crash events are associated with high driver alertness, not with driver drowsiness (Wiegand et al., 2008).  Further, these non-crash events do not validly represent serious crash risk (Knipling, 2017).

Why is this argument important?  It’s because the government puts too many resources into policing truck and bus driver hours-of-driving, and not enough into ensuring that those same drivers are medically qualified, getting sufficient sleep, educated on risks, and managed based on an understanding of sleep-alertness physiology.  It’s also important because regular motorists might worry too much about how many hours they drive and not enough about the physiological and lifestyle ingredients they need to stay awake.
 

Cited References

AAA Foundation for Traffic Safety [Author: B. C. Tefft].  Acute Sleep Deprivation and Risk of Motor Vehicle Crash Involvement.  Fact Sheet.  2018.  Available at AAAFoundation.org.  

Blanco, M., Hanowski, R. J., Olson, R.L., Morgan, J. F., Soccolich, S. A., Wu, S-C, and Guo, F. The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations. Report No. FMCSA-RRR-11-017. Wash. DC: DoT. 2011.

Dawson, D. & Reid, K.  Fatigue, alcohol and performance impairment.  Nature. Vol 388, 17 July 1997.

Dinges, D. F., Mallis, M.M., Maislin, G.M., and Powell, J.W.  Evaluation of Techniques for Ocular Measurement as an Index of Fatigue and the Basis for Alertness Management.  NHTSA Report No. DOT HS 808 762, April, 1998.

Jovanis, P. P. Wu, K-F., Chen, C. (2011) Hours of service and driver fatigue: driver characteristics research, Report No. FMCSA-RRR-11-018, U.S. DOT. 

Knipling, R.R.  Safety for the Long Haul; Large Truck Crash Risk, Causation, & Prevention.  American Trucking Associations.  ISBN 978-0-692-00073-1, 2009.  Information available at www.safetyforthelonghaul.com.

Knipling, R.R. Threats to scientific validity in truck driver hours-of-service studies. Proceedings of the 9th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, Pp. 382-388, Manchester Village VT, June 26-29, 2017.

Tefft, B.C.  Acute sleep deprivation and culpable motor vehicle crash involvement.  SLEEPJ, Pp.  1–11, 2018.  Available at: https://academic.oup.com/sleep/article/41/10/zsy144/5067408.

Wiegand, D.M., R. J. Hanowski, R. L. Olson, and W. Melvin. (2008) Fatigue analyses from 16 months of naturalistic commercial motor vehicle driving data, The National Surface Transportation Center for Excellence. Available at: http://scholar.lib.vt.edu/VTTI/reports/FatigueAnalyses_061208.pdf.

Wylie, C.D., Shultz, T., Miller, J.C., Mitler, M.M., & Mackie, R.R., Commercial Motor Vehicle Driver Fatigue and Alertness Study, FHWA-MC-97-002, Federal Highway Administration, U.S. Department of Transportation, Washington, DC, 1996.

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