Real-time Nonintrusive Detection of Driver Drowsiness

Driver drowsiness is one of the major causes of serious traffic accidents, which makes this an area of great socioeconomic concern. Continuous monitoring of drivers’ drowsiness thus is of great importance to reduce drowsiness-caused accidents. This proposed research developed a real-time, nonintrusive driver drowsiness detection system by building biosensors on the automobile steering wheel and driver’s seat to measure driver’s heart beat signals. Heart rate variability (HRV), a physiological signal that has established links to waking/sleepiness stages, is analyzed from the heat beat pulse signals for the detection of driver drowsiness. The novel design of measuring heat beat signal from biosensors on the steering wheel means this drowsiness detection system has almost no annoyance to the drivers, and the use of a physiological signal can ensure the drowsiness detection accuracy.

[1]  Hiroshi Ueno,et al.  Development of drowsiness detection system , 1994, Proceedings of VNIS'94 - 1994 Vehicle Navigation and Information Systems Conference.

[2]  Aaron Steinfeld,et al.  A user-centered drowsy-driver detection and warning system , 2003, DUX '03.

[3]  Jayne Gackenbach.  Sleep and Dreams : A Sourcebook , 1986 .

[4]  Jennifer Healey,et al.  Detecting stress during real-world driving tasks using physiological sensors , 2005, IEEE Transactions on Intelligent Transportation Systems.

[5]  M. Chung,et al.  Electroencephalographic study of drowsiness in simulated driving with sleep deprivation , 2005 .

[6]  王成焘,et al.  Power Spectral Analysis of Heart Rate Variability of Driver Fatigue , 2005 .

[7]  S. Honma,et al.  Effects of light and sleep stages on heart rate variability in humans , 2001, Psychiatry and clinical neurosciences.

[8]  Sergio Cerutti,et al.  Spectral analysis of heart rate variability signal during sleep stages , 1994, Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  M. Bonnet,et al.  Heart rate variability: sleep stage, time of night, and arousal influences. , 1997, Electroencephalography and clinical neurophysiology.

[10]  Paul Stephen Rau,et al.  Drowsy Driver Detection and Warning System for Commercial Vehicle Drivers: Field Operational Test Design, Data Analyses, and Progress , 2005 .

[11]  N Egelund,et al.  Spectral analysis of heart rate variability as an indicator of driver fatigue. , 1982, Ergonomics.

[12]  Mark R Rosekind,et al.  Underestimating the societal costs of impaired alertness: safety, health and productivity risks. , 2005, Sleep medicine.

[13]  M. Dumont,et al.  A study of the dynamic interactions between sleep EEG and heart rate variability in healthy young men , 2003, Clinical Neurophysiology.

[14]  Ashley Craig,et al.  Development of an algorithm for an EEG-based driver fatigue countermeasure. , 2003, Journal of safety research.

[15]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[16]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[17]  Zhiwei Zhu,et al.  Real-time nonintrusive monitoring and prediction of driver fatigue , 2004, IEEE Transactions on Vehicular Technology.

[18]  G. Zaccara,et al.  Human heart rate variability and sleep stages , 1996, The Italian Journal of Neurological Sciences.

[19]  R P Hamlin.  THREE-IN-ONE VEHICLE OPERATOR SENSOR , 1995 .

[20]  W C Orr,et al.  Heart rate variability during waking and sleep in healthy males and females. , 1999, Sleep.

[21]  K. Todd,et al.  Drowsy driving and automobile crashes , 1998 .

[22]  N.V. Thakor,et al.  Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection , 1991, IEEE Transactions on Biomedical Engineering.

[23]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[24]  S Milosević,et al.  Drivers' fatigue studies. , 1997, Ergonomics.

[25]  Tzyy-Ping Jung,et al.  EEG-based drowsiness estimation for safety driving using independent component analysis , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.

[26]  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 .

[27]  Wang Rongben,et al.  Driver's eye state detecting method design based on eye geometry feature , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[28]  R Lazzara,et al.  Heart rate variability during specific sleep stages. A comparison of healthy subjects with patients after myocardial infarction. , 1995, Circulation.