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A Novel Application of Inertial Measurement Units (IMUs) as Vehicular Technologies for Drowsy Driving Detection via Steering Wheel Movement

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DOI: 10.4236/ojsst.2014.44018    5,313 Downloads   5,853 Views   Citations


Introduction: Vehicular technologies intended for the improvement of driver safety are especially critical today in the view of the thousands of deaths that occur annually due to drowsy driving. Current technologies include physiological methods like electroencephalography (EEG), behavioral methods including driver video monitoring, and vehicle measures which include lane and steering wheel tracking. These current technologies are impractical in their current implementations as they cannot readily be used outside of laboratory settings due to their requirements for intrusive electrodes, expensive cameras, and complex equipment. An earlier article demonstrated an effective method for wheel tracking using only an accelerometer; however the introduction of integrated gyroscopes and accelerometers has afforded further opportunities. Objective: This paper introduces a novel, low-cost, and easy to implement an approach to address this unmet problem. Method: Through the use of an Inertial Measurement Unit (IMU) combining a gyroscope and an accelerometer, measurements of steering wheel behavior were recorded in both simulator and real world driving while compared against a standard potentiometer. Results: The excellent agreement between potentiometer recorded angles and IMU estimated angles (R2 = 0.98, P < 0.001) suggests that the complicated installation of potentiometers in vehicle steering columns is no longer a necessary step for steering wheel monitoring. Conclusion: This paper presents an IMU based method for drowsy steering-wheel behavioral tracking which is cost-effective, easy to implement, and accurately estimates steering behaviors. The results suggest that this novel vehicle technology offers hope for improving road safety.

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The authors declare no conflicts of interest.

Cite this paper

Lawoyin, S. , Fei, D. and Bai, O. (2014) A Novel Application of Inertial Measurement Units (IMUs) as Vehicular Technologies for Drowsy Driving Detection via Steering Wheel Movement. Open Journal of Safety Science and Technology, 4, 166-177. doi: 10.4236/ojsst.2014.44018.


[1] Rau, P. (1996) NHTSA’s Drowsy Driver Research Program. National Highway Traffic Safety Administration. Washington DC.
[2] Vanlaar, W., Simpson, H., Mayhew, D. and Robertson, R. (2008) Fatigued and Drowsy Driving: A Survey of Attitudes, Opinions and Behaviors. Journal of Safety Research, 39, 303-309.
[3] Connor, J., Norton, R., Ameratunga, S., Robinson, E., Civil, I., Dunn, R., Bailey, J. and Jackson, R. (2002) Driver Sleepiness and Risk of Serious Injury to Car Occupants: Population Based Case Control Study. BMJ, 324, 1125.
[4] Hamblin, P. (1987) Lorry Driver’s Time Habits in Work and Their Involvement in Traffic Accidents. Ergonomics, 30, 1323-1333.
[5] Maclean, A.W., Davies, D.R. and Thiele, K. (2003) The Hazards and Prevention of Driving While Sleepy. Sleep Medicine Reviews, 7, 507-521.
[6] Kim, J.Y., Jeong, C.H., Jung, M.J., Park, J.H. and Jung, D.H. (2013) Highly Reliable Driving Workload Analysis Using Driver Electroencephalogram (EEG) Activities during Driving. International Journal of Automotive Technology, 14, 965-970.
[7] Ogawa, K. and Shimotani, M. (1997) A Drowsiness Detection system. Mitsubishi Electric Advance, 78, 13-16.
[8] Wierwille, W. (1999) Historical Perspective on Slow Eyelid Closure: Whence PERCLOS? In: Technical Proceedings of Ocular Measures of Driver Alertness Conference, Herndon, VA (FHWA Technical Report No. MC-99-136), Federal Highway Administration, Office of Motor Carrier and Highway Safety, Washington DC, 31-53.
[9] Bowman, D.S., Schaudt, W.A. and Hanowski, R.J. (2012) Advances in Drowsy Driver Assistance Systems through Data Fusion. In: Handbook of Intelligent Vehicles, Springer, Berlin, 895-912.
[10] Wierwille, W., Hanowski, R., Olson, R., Dinges, D., Price, N., Maislin, G., Powell IV, J., Ecker, A., Mallis, M. and Szuba, M. (2003) NHTSA Drowsy Driver Detection and Interface Project-Final Report. Contract No. DTNH22-D- 00-07007, Task Order, 1.
[11] Fukuda, J., Akutsu, E. and Aoki, K. (1995) An Estimation of Driver’s Drowsiness Level Using Interval of Steering Adjustment for Lane Keeping. JSAE Review, 16, 197-199.
[12] Elling, M. and Sherman, P. (1994) Evaluation of Steering Wheel Measures for Drowsy Drivers. Proceedings of the 27th ISATA, Aachen, 31 October-4 November 1994, 207-214.
[13] Thiffault, P. and Bergeron, J. (2003) Monotony of Road Environment and Driver Fatigue: A Simulator Study. Accident Analysis & Prevention, 35, 381-391.
[14] Eskandarian, A. and Mortazavi, A. (2007) Evaluation of a Smart Algorithm for Commercial Vehicle Driver Drowsi- ness Detection. Proceedings of IEEE Conference on Intelligent Vehicles Symposium, Istanbul, 13-15 June 2007, 553- 559.
[15] Yabuta, K., Iizuka, H., Yanagishima, T., Kataoka, Y. and Seno, T. (1985) The Development of Drowsiness Warning Devices. Proceedings of the 10th International Technical Conference on Experimental Safety Vehicles (ESV), Oxford, England, 10, 282-288.
[16] Sayed, R. and Eskandarian, A. (2001) Unobtrusive Drowsiness Detection by Neural Network Learning of Driver Steering. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 215, 969-975.
[17] Luinge, H., Veltink, P. and Baten, C. (1999) Estimating Orientation with Gyroscopes and Accelerometers. Technology and Health Care, 7, 455-459.
[18] Lee, H., Ryu, S. and Lee, J. (2009) Optimal Posture of Mobile Inverted Pendulum Using a Single Gyroscope and Tilt Sensor. Proceedings of ICCAS-SICE, Fukuoka, 18-21 August 2009, 865-870.
[19] Greene, M. (1996) A Solid State Attitude Heading Reference System for General Aviation. Proceedings of IEEE Conference on Emerging Technologies and Factory Automation, Kauai, 18-21 November 1996, 413-417.
[20] Lawoyin, S.A., Fei, D.Y. and Bai, O. (2014) Accelerometer-Based Steering Wheel Movement Monitoring for Drowsy Driving Detection. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Published Online 31 October 2014.
[21] Sakaguchi, T., Kanamori, T. and Katayose, H. (1996) Human Motion Capture by Integrating Gyroscopes and Accelerometers. Proceedings of IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems, Washington DC, 8-11 December 1996, 470-475.

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