This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Feasibility Study of Drowsy Driving Prediction based on Eye Opening Time
Technical Paper
2017-01-1398
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
Since drowsy driving is a major cause of serious traffic accidents, there is a growing requirement for drowsiness prevention technologies. This study proposes a drowsy driving prediction method based on eye opening time. One issue of using eye opening time is predicting strong drowsiness before the driver actually feels sleepy. Because overlooking potential hazards is one of the causes of traffic accidents and is closely related to driver cognition and drowsiness, this study focuses on eye opening movements during driving. First, this report describes hypotheses concerning drowsiness and eye opening time based on the results of previous studies. It is assumed that the standard deviation of eye opening time (SDEOP) indicates driver drowsiness and the following two transitions are considered: increasing and decreasing SDEOP. To confirm the hypotheses, the relationship between drowsiness and SDEOP was investigated. The two transitions were observed in preliminary experiments on a test course (number of drivers: 7, speed: 80 km/h). A drowsy driving prediction method was then developed based on the hypotheses. The proposed method has upper and lower thresholds, and predicts drowsiness when SDEOP crosses one of the thresholds. The thresholds are determined by an adaptation session to address individual differences in SDEOP. Finally, experiments on the test course (number of drivers: 10, speed: 80 km/h) confirmed that this method has the potential to predict strong drowsiness 5 to 25 minutes in advance.
Recommended Content
Technical Paper | Improvement of Blind Spot Alert Detection by Elderly Drivers |
Technical Paper | Cognitive Awareness of Intelligent Vehicles |
Technical Paper | A Study on Car Following and Cognitive Ability of Elderly Drivers by Using Driving Simulator |
Authors
Citation
Hatakeyema, Y., "Feasibility Study of Drowsy Driving Prediction based on Eye Opening Time," SAE Technical Paper 2017-01-1398, 2017, https://doi.org/10.4271/2017-01-1398.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 | ||
Unnamed Dataset 3 | ||
Unnamed Dataset 4 |
Also In
References
- Research on Drowsy Driving Jul. 2016
- Fukuda , J. , Akutsu , E. , Aoki , K. Estimation of driver’s drowsiness level using interval of steering adjustment for lane keeping JSAE Review 16 2 1917 1919 1995
- Humpt , D. , Honzik , P. , Raso , P. , Hyncica , O. Steering wheel motion analysis for detection of the driver’s drowsiness MACMESE 2011 Italy November 3-5, 2011
- McDonald , D.A. , Schwarz , C. , Brown , D.J. , Brown , L.T. Real-Time Detection of Drowsiness Related Lane Departures Using Steering Wheel Angle Proceedings of the Human Factors and Ergonomics Society Annual Meeting 56 2201 2205 2012 10.1177/1071181312561464
- Sayed , R. , Eskandarian , A. Unobtrusive drowsiness detection by neural network learning of driver steering Proceedings of the Institution of Mechanical Engineering 215 9 969 975 2001 10.1243/0954407011528536
- Leng , H. , Lin , Y. , Mourant , R. An Experimental Study Using EEG to Detect Driver Drowsiness Commercial Vehicle Engineering Congress & Exhibition 2008 10.4271/2008-01-2693
- Makeig , S. , Jung , T. Changes in alertness are a principal component of variance in the EEG spectrum NeuroReport 7 213 216 1995 10.1097/00001756-199512000-00051
- Byeon , M. , Han , S. , Min , H. , Wo , Y. , Park , Y. , Huh , W. A study of HRV analysis to detect drowsiness states of drivers Proceedings of the Fourth IASTED International Conference on Biomedical Engineering 2006 153 155 2006
- Sato , S. , Taoda , K. , Kawamura , M. , Wakaba , K. , Fukuchi , Y. , Nishiyama , K. Heart rate variability during long truck driving work Journal of Human Ergology 30 235 240 2001
- Hayashi , K. , Ishihara , K. , Hashimoto , H. , Oguri , K. Individualized drowsiness detection during driving by pulse wave analysis with neural network Proceedings of IEEE Conference on Intelligent Transportation Systems 2005 901 906 2005 10.1109/ITSC.2005.1520170
- Lee , Y. , Yoon , S. , Lee , C. , Lee , M. Wearable EDA sensor gloves using conducting fabric and embedded system Proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology 6785 6788 2006 10.1109/IEMBS.2006.260947
- Vural , E. , Cetin , M. , Ereil , A. , Littlewort , G. , Bartlett , M. , Movellan , J. Drowsy driver detection through facial movement analysis Proceedings of Human-Computer Interaction - IEEE International Workshop 6 18 2007 10.1007/978-3-540-75773-3_2
- Wang , W. , Qin , H. A FPGA based driver drowsiness detecting system Proceedings of 2005 IEEE International Conference on Vehicular Electronics and Safety 358 363 2005
- Yang , Y. , Sheng , J. , Zhou , W. The monitoring method of driver’s fatigue based on neural network Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation 3555 3559 2007
- Pentland , A. , Mognanddam , B. , Starner , T. View based and modular eigenspaces for face recognition Proceedings of Int. Conference on Computer Vision and Pattern Recognition 756 761 1994 10.1109/CVPR.1994.323814
- Huang , J. , Wechsler , H. Visual routines for eye localization using learning and evolution IEEE Trans. Evol. Comput. 4 1 73 82 2000
- Song , J. , Chi , Z. , Liu. , J. A robust eye detection method using combined binary edge and intensity information Pattern Recognition 39 1110 125 2006 10.1016/j.patcog.2005.11.015
- Kawaguchi , T. , Rizon , M. Iris detection using intensity and edge information Pattern Recognition 36 549 62 2003 10.1016/S0031-3203(02)00066-3
- Shirakata , T. , Tanida , K. , Nishiyama , J. , Hirata , Y. Detect the Imperceptible Drowsiness SAE Int. J. Passeng. Cars - Electron. Electr. Syst. 3 1 98 108 10.4271/2010-01-0746
- Jarvis , R. Intelligent sensor based road vehicle driver assistance: Inclusion of vision based drowsiness and inattention monitoring Recent Advances in Circuits, Systems and Signal Processing 314 319 2002
- Sakai , H. , Shin , D. , Uchiyama Y. , Terashima R. , Wakita T. Slow eye movement as a possible predictor of reaction delays to auditory warning alarms in a drowsy state Ergonomics 54 2 146 53 2011 10.1080/00140139.2010.538724
- Hamada , T. , Adachi , K. , Nakano , T. , Yamamoto , S. Detecting Method Applicable to Individual Features for Drivers’ Drowsiness IEICE Transactions on Information and Systems E87-D 1 89 96 2004
- Skipper , J. , Wierwille , W. Drowsy Driver Detection Using Discriminant Analysis Human Factors 28 5 527 540 1986
- Park , I. , Ahn , J. , Byun , H. Efficient measurement of the eye blinking by using decision function for intelligent vehicles Proceedings of 7th Computational Science International Conference 546 549 2007 10.1007/978-3-540-72590-9_75
- Tijeriana , L. , Glecker , M. , Stoltzfus , D. , Johnson , S. , Goodman , M J. , Wierwille , W. A preliminary Assessment of Algorithm for Drowsy and Inattentive Driver Detection on the Road National Highway Traffic Safety Administration HS-808 905 1998
- Dinges , D. , Grace , R. PERCLOS: A Valid Psychophysiological Measure of Alertness As Assessed by Psychomotor Vigilance TechBrief NHTSA 1998
- Trutschel , U. , Sirois , B. , Sommer , D. , Golz , M. , Edwards , D. PERCLOS: An Alertness Measure of the Past Proceedings of the Sixth International Driving Symposium on Human Factors in Driver Assessment Training and Vehicle Design 172 179
- Raichle , M.E. , MacLeod , A.M. , Snyder , A.Z. , Powers , W.J. , Gusnard , D.A. , Shulman , G.L. A default mode of brain function Proceedings of the National Academy of Sciences of the United States of America 98 676 682 2001 10.1073/pnas.98.2.676
- Gusnard , D.A. , Akbudak , E. , Shulman , G.L. , Raichle , M.E. Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function Proceedings of the National Academy of Sciences of the United States of America 98 4259 4264 2001 10.1073/pnas.071043098
- Amodio , D.M. , Frith , C.D. Meeting of minds: the medial frontal cortex and social cognition Nature Reviews Neuroscience 7 268 277 2006 10.1038/nrn1884
- Mason , M.F. , Norton , M.I. , Van Horn , J.D. , Wegner , D.M. , Grafton , S.T. , Macrae , C.N. Wandering minds: the default network and stimulus-independent thought Science 315 393 395 2007 10.1126/science.1131295
- Raichle , M.E. The Brain’s Dark Energy Scientific American Mar. 2010
- Nakano , T. , Kato , M. , Morito , Y. , Itoi , S. , Kitazawa , S. Blink-related momentary activation of the default mode network while viewing videos Proceedings of the National Academy of Sciences of the United States of America 110 702 706 2013 10.1073/pnas.1214804110
- Nakano , T. , Yamamoto , Y. , Kitajo , K. , Takahashi , T. , Kitazawa , S. Synchronization of spontaneous eyeblinks while viewing video stories Proceedings of the Royal Society B: Biological Sciences 276 3635 3644 2009 10.1098/rspb.2009.0828
- Fox , M.D. , Snyder , A.Z. , Vincent , J.L. , Corbetta , M. , Van Essen , D.C. , Raichle , M.E. The human brain is intrinsically organized into dynamic, anticorrelated functional networks Proceedings of the National Academy of Sciences of the United States of America 102 9673 9678 2005 10.1073/pnas.0504136102
- Obinata G. Nap Sign Detection during Driving Automobiles” (in Japanese Journal of the Japan Society of Mechanical Engineering 116 1140 24 27 2013
- Institute for Traffic Accident Research and Data Analysis ITARDA Information 33
- Traffic Planning Division of National Police Agency of Japan Public information document http://www.driveplaza.com/special/letsbreak/pdf/letsbreak_press.pdf Nov. 2014
- Hiroki , K. , Nakaho , N. , Keiichi , Y. , Yoshihiro G. Prediction of Automobile Driver Sleepiness (1st Report, Rating of Sleepiness Based on Facial Expression and Examination of Effective Predictor Indexes of Sleepiness)” (in Japanese) The Japan Society of Mechanical Engineers Journal (Series C) 63 613 93 100 1997
- Hanowski , R. , Bowman , D. , Alden , A. , Wierwille , W. et al. PERCLOS+:Moving Beyond Single-Metric Drowsiness Monitors SAE Technical Paper 2008-01-2692 2008 10.4271/2008-01-2692