Monitoring Task Fatigue in Contemporary and Future Vehicles: A Review

This article reviews advancements in methods for detection of task-induced driver fatigue. Early detection of the onset of fatigue may be enhanced by spectral frequency analysis of the electrocardiogram (ECG) and analysis of eye fixation durations. Validity may also be improved by developing algorithms that accommodate driver sleep history assessed using mobile actigraphic methods. Challenges to development of fatigue indices include ensuring that metrics are valid across the range of task demands encountered by drivers. Future autonomous vehicles will place novel demands on the driver, and research is needed to test the applicability of current fatigue metrics.

[1]  C. Guilleminault,et al.  Fatigue, sleep restriction and driving performance. , 2005, Accident; analysis and prevention.

[2]  Robert Schleicher,et al.  Driving without Awareness: Examination of the Phenomenon , 2006 .

[3]  Elisabeth Schmidt,et al.  Correlation between subjective driver state measures and psychophysiological and vehicular data in simulated driving , 2016, 2016 IEEE Intelligent Vehicles Symposium (IV).

[4]  Pablo Laguna,et al.  Drowsiness detection using heart rate variability , 2016, Medical & Biological Engineering & Computing.

[5]  Peter Nickel,et al.  Sensitivity and Diagnosticity of the 0.1-Hz Component of Heart Rate Variability as an Indicator of Mental Workload , 2003, Hum. Factors.

[6]  Lauren Reinerman-Jones,et al.  Metrics for individual differences in EEG response to cognitive workload: Optimizing performance prediction , 2017 .

[7]  Sheldon M. Russell,et al.  Alternative Indices of Performance: An Exploration of Eye Gaze Metrics in a Visual Puzzle Task , 2014 .

[8]  James F. O'Hanlon,et al.  Heart Rate Variability: A New Index of Driver Alertness/Fatigue , 1972 .

[9]  Peter Rossiter,et al.  Applying neural network analysis on heart rate variability data to assess driver fatigue , 2011, Expert Syst. Appl..

[10]  John Yuan,et al.  Changes in Physiological Parameters Induced by Indoor Simulated Driving: Effect of Lower Body Exercise at Mid-Term Break , 2009, Sensors.

[11]  T H Monk,et al.  Wrist actigraphic measures of sleep in space. , 1999, Sleep.

[12]  R J Fairbanks,et al.  RESEARCH ON VEHICLE-BASED DRIVER STATUS/PERFORMANCE MONITORING; DEVELOPMENT, VALIDATION, AND REFINEMENT OF ALGORITHMS FOR DETECTION OF DRIVER DROWSINESS. FINAL REPORT , 1994 .

[13]  Edward M. Hitchcock,et al.  Active and passive fatigue in simulated driving: discriminating styles of workload regulation and their safety impacts. , 2013, Journal of experimental psychology. Applied.

[14]  Jinchao Lin,et al.  Considerations in Physiological Metric Selection for Online Detection of Operator State: A Case Study , 2016, HCI.

[15]  Catherine Neubauer,et al.  Fatigue in the Automated Vehicle , 2014 .

[16]  S D Baulk,et al.  Effects of moderate sleep deprivation and low-dose alcohol on driving simulator performance and perception in young men. , 2007, Sleep.

[17]  Evangelos Bekiaris,et al.  Using EEG spectral components to assess algorithms for detecting fatigue , 2009, Expert Syst. Appl..

[18]  Zhixia Li,et al.  Threshold Research on Highway Length under Typical Landscape Patterns Based on Drivers’ Physiological Performance , 2015 .

[19]  Sara Mariani,et al.  Validity of a commercial wearable sleep tracker in adult insomnia disorder patients and good sleepers. , 2017, Journal of psychosomatic research.

[20]  Heidi Kloos,et al.  Voluntary behavior in cognitive and motor tasks , 2010 .

[21]  D. Kripke,et al.  The role of actigraphy in the evaluation of sleep disorders. , 1995, Sleep.

[22]  Kenneth Sundaraj,et al.  Drowsiness detection during different times of day using multiple features , 2013, Australasian Physical & Engineering Sciences in Medicine.

[23]  Job G. Godino,et al.  Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents , 2016, Physiology & Behavior.

[24]  Gerald Matthews,et al.  Dangerous intersections? A review of studies of fatigue and distraction in the automated vehicle. , 2019, Accident; analysis and prevention.

[25]  G. Matthews.  Towards a transactional ergonomics for driver stress and fatigue , 2002 .

[26]  R. Schleicher,et al.  Blinks and saccades as indicators of fatigue in sleepiness warners: looking tired? , 2022 .

[27]  Micheal Drieberg,et al.  A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability , 2017, Sensors.

[28]  G. Borghini,et al.  Neuroscience and Biobehavioral Reviews , 2022 .

[29]  Mario Muñoz-Organero,et al.  Predicting Upcoming Values of Stress While Driving , 2017, IEEE Transactions on Intelligent Transportation Systems.

[30]  D F Kripke,et al.  Wrist-actigraphic estimation of sleep time. , 1980, Sleep.

[31]  Luciane L. de Souza,et al.  Further validation of actigraphy for sleep studies. , 2003, Sleep.

[32]  Rebecca L Olson,et al.  The sleep of commercial vehicle drivers under the 2003 hours-of-service regulations. , 2007, Accident; analysis and prevention.

[33]  R. Norton,et al.  Driver sleepiness and risk of serious injury to car occupants: population based case control study , 2002, BMJ : British Medical Journal.

[34]  Chongxun Zheng,et al.  Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator. , 2012, Accident; analysis and prevention.

[35]  Hong Wang,et al.  A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors , 2017 .

[36]  Kun Jiao,et al.  Effect of different vibration frequencies on heart rate variability and driving fatigue in healthy drivers , 2004, International archives of occupational and environmental health.

[37]  Linden J. Ball,et al.  Eye tracking in HCI and usability research. , 2006 .

[38]  Peter A. Hancock,et al.  ACTIVE AND PASSIVE FATIGUE STATES , 2001 .

[39]  J. Kientz,et al.  Consumer Sleep Technologies: A Review of the Landscape. , 2015, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

[40]  Gerald Matthews,et al.  Multidimensional Profiling of Task Stress States for Human Factors , 2016, Hum. Factors.

[41]  Carryl L. Baldwin,et al.  Driver fatigue: The importance of identifying causal factors of fatigue when considering detection and countermeasure technologies , 2009 .

[42]  W. Dement,et al.  Quantification of sleepiness: a new approach. , 1973, Psychophysiology.

[43]  Catherine Neubauer,et al.  The Effects of Cell Phone Use and Automation on Driver Performance and Subjective State in Simulated Driving , 2012 .

[44]  J. Ware,et al.  Medical Resident Driving Simulator Performance Following a Night on Call , 2006, Behavioral sleep medicine.

[45]  A. Baharav,et al.  Early detection of falling asleep at the wheel: A Heart Rate Variability approach , 2008, 2008 Computers in Cardiology.