Effect of Circadian Rhythms and Driving Duration on Fatigue Level and Driving Performance of Professional Drivers

Circadian rhythms, inherent in all humans, consist of 24-h biological patterns that affect a person's fatigue level. The effect of circadian rhythms on driving performance was explored in an on-road driving study. Fifteen middle-aged professional daytime drivers were recruited to participate in the experiment. Participants were classified into three groups: (a) a morning group that started driving at 09:00, (b) a noon group that started driving at 12:00, and (c) an evening group that started driving at 21:00. Each group completed a 6-h driving task. The self-reported Karolinska sleepiness scale score was recorded every 5 min, and data on driving performance parameters, such as steering and lane positioning, were also acquired. The results indicated that both circadian rhythms and driving duration had significant effects on self-reported fatigue levels and that the fatigue level increased faster in the evening group than the morning and noon groups. The results of the circadian rhythm analysis showed that a driver was most likely to feel tired between 14:00 and 16:00 and between 02:00 and 04:00, when the ability to stay within designated lane lines (lane maintenance) was significantly impaired for drivers in all three groups. The evening group drivers were the most at risk. The steering performance did not show a significant relationship with the self-reported fatigue level. The self-reported fatigue level is the result of the interactive effect of circadian rhythms and driving duration. The standard deviation of lane position was more correlated with circadian rhythms than with the steering reversal rate.

[1]  Riccardo Rossi,et al.  Analysis of driver task-related fatigue using driving simulator experiments , 2011 .

[2]  Fabio Pizza,et al.  Daytime driving simulation performance and sleepiness in obstructive sleep apnoea patients. , 2008, Accident; analysis and prevention.

[3]  Paul P Jovanis,et al.  Effects of Hours of Service and Driving Patterns on Motor Carrier Crashes , 2012 .

[4]  J. W. Spencer,et al.  Chromatic analysis of signals from a driver fatigue monitoring unit , 2007 .

[5]  T. Åkerstedt,et al.  Subjective and objective sleepiness in the active individual. , 1990, The International journal of neuroscience.

[6]  Teng Jing Experimental Study of Fatigue Characteristics of Bus Drivers Under the Condition of Continuous Driving , 2013 .

[7]  Simon G Hosking,et al.  Predicting driver drowsiness using vehicle measures: recent insights and future challenges. , 2009, Journal of safety research.

[8]  N. Maurits,et al.  Impaired driving simulation in patients with Periodic Limb Movement Disorder and patients with Obstructive Sleep Apnea Syndrome. , 2012, Sleep medicine.

[9]  T. Brown,et al.  Driving Performance and Obstructive Sleep Apnea , 2009 .

[10]  Yan Xinping,et al.  Research Progress and Prospect of Road Traffic Driving Behavior , 2013 .

[11]  Natasha Merat,et al.  The effect of three low-cost engineering treatments on driver fatigue: A driving simulator study. , 2013, Accident; analysis and prevention.

[12]  Susan B. Van Hemel,et al.  Effects of Cargo Loading and Unloading on Truck Driver Alertness , 1999 .

[13]  Helen Sutherland,et al.  The Royal Society for the Prevention of Accidents , 1950 .

[14]  R. Croft,et al.  Cognitive components of simulated driving performance: Sleep loss effects and predictors. , 2013, Accident; analysis and prevention.

[15]  D Royal,et al.  VOLUME I: FINDINGS -- NATIONAL SURVEY OF DISTRACTED AND DROWSY DRIVING ATTITUDES AND BEHAVIORS: 2002 , 2003 .

[16]  J. Bergeron,et al.  Fatigue and individual differences in monotonous simulated driving , 2003 .

[17]  Linda Ng Boyle,et al.  Commercial Driver Factors in Run-off-Road Crashes , 2012 .

[18]  Brian C Tefft,et al.  The Prevalence and Impact of Drowsy Driving , 2010 .