Sensitivity of Lane Position and Steering Angle Measurements to Driver Fatigue

The parameter value chosen to measure driving performance affects the accuracy of the estimated fatigue level. Methods to analyze the sensitivity of these parameter values were proposed. Standard deviation of lane position (SDLP) and steering reversal rate (SRR) were considered to assess fatigue, and the sensitivity of these parameters was analyzed from the time domain and value domain. Thirty-six male drivers participated in a field test. Lane position, steering wheel angle data, and self-reported fatigue level (scored on the Karolinska sleepiness scale) were recorded. SDLP results indicate that the maximum average coefficient with fatigue level reached .11, with a unified statistical interval of 202 s when the consecutive analysis method was used; the maximum average coefficient was .12 with a unified interval of 120 s when the maximum analysis method was used. SRR results indicate that a steering angle difference of 6° was the most sensitive threshold for driver fatigue level and has an average correlation coefficient of .42, which demonstrated that SRR was more reliable than SDLP for monitoring fatigue level. With the use of the optimal parameter value, the variation results of SDLP and SRR at each fatigue level were examined, and results indicate that driving ability was impaired as fatigue level increased. The methods and results can be applied to analyses of fatigued or drowsy driving.

[1]  M. Golz,et al.  Evaluation of PERCLOS based current fatigue monitoring technologies , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

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

[3]  G Renner,et al.  LANE DEPARTURE AND DROWSINESS - TWO MAJOR ACCIDENT CAUSES - ONE SAFETY SYSTEM , 1997 .

[4]  Fred S. Switzer,et al.  Lane heading difference: An innovative model for drowsy driving detection using retrospective analysis around curves. , 2015, Accident; analysis and prevention.

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

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

[7]  Jacques Bergeron,et al.  Monotony of road environment and driver fatigue: a simulator study. , 2003, Accident; analysis and prevention.

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

[9]  Pierre Philip,et al.  Reliability of simulator driving tool for evaluation of sleepiness, fatigue and driving performance. , 2012, Accident; analysis and prevention.

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

[11]  Ulla Kaisa Knutsson SWEDISH NATIONAL ROAD AND TRANSPORT RESEARCH INSTITUTE , 2003 .

[12]  Tzyy-Ping Jung,et al.  Tonic and phasic EEG and behavioral changes induced by arousing feedback , 2010, NeuroImage.

[13]  Darrell S Bowman,et al.  Development and Assessment of a Driver Drowsiness Monitoring System , 2012 .

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

[15]  Xinping Yan,et al.  Effect of Circadian Rhythms and Driving Duration on Fatigue Level and Driving Performance of Professional Drivers , 2014 .

[16]  T. Jung,et al.  Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness. , 1996, Brain research. Cognitive brain research.

[17]  Tal Oron-Gilad,et al.  Alertness maintaining tasks (AMTs) while driving. , 2008, Accident; analysis and prevention.

[18]  Tzyy-Ping Jung,et al.  Cell-phone based Drowsiness Monitoring and Management system , 2012, 2012 IEEE Biomedical Circuits and Systems Conference (BioCAS).

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

[20]  Riccardo Rossi,et al.  Effects of driver task-related fatigue on driving performance , 2014 .

[21]  Jesper Sandin,et al.  Vehicle control and drowsiness , 2002 .

[22]  Udo Trutschel,et al.  PERCLOS: An Alertness Measure of the Past , 2017 .

[23]  Xuesong Wang,et al.  Driver drowsiness detection based on non-intrusive metrics considering individual specifics. , 2016, Accident; analysis and prevention.

[24]  Abhi R. Varma,et al.  Accident Prevention Using Eye Blinking and Head Movement , 2012 .

[25]  M. Jeng,et al.  Driver fatigue and highway driving: A simulator study , 2008, Physiology & Behavior.