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Drowsiness Warning System Using Artificial Intelligence

Authors: Nidhi Sharma, V. K. Banga

Abstract:

Nowadays, driving support systems, such as car navigation systems, are getting common, and they support drivers in several aspects. It is important for driving support systems to detect status of driver's consciousness. Particularly, detecting driver's drowsiness could prevent drivers from collisions caused by drowsy driving. In this paper, we discuss the various artificial detection methods for detecting driver's drowsiness processing technique. This system is based on facial images analysis for warning the driver of drowsiness or in attention to prevent traffic accidents.

Keywords: Neuro-Fuzzy Model, Halstead Model, Walston-FelixModel, Bailey-Basili Model, Doty Model, GA Based Model, GeneticAlgorithm.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1080382

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References:


[1] T. Hamada, T. Ito, K. Adachi, T. Nakano, and S. Yamamoto (2003),"Detecting method for Driver-s drowsiness applicable to Individual Features" IEEE proc. Intelligent Transportation Systems, vol. 2, pp.1405-1410.
[2] L. Barr, H. Howrach, S. Popkin and R. J. Carroll (2009) " A review and evaluation of emerging driver fatigue detection, measures and technologies", A Report of US department of transportation, Washington DC, USA.
[3] M. Eriksson and N.P. Papanikolopoulos, (1997), "Eye-tracking for detection of driver fatigue", IEEE proc. Intelligent Transport System, Boston, MA, pp. 314-319.
[4] A. Eskandarian, and A. Mortazavi (2007), "Evaluation of a smart algorithm for commercial vehicle driver drowsiness detection", IEEE Intelligent Vehicles Symposium (IV'07), Istanbul, Turkey, pp. 553-559.
[5] H. Gu, Y. Zhang, and Qiang Ji, (2005), "Task oriented facial behaviour recognition with selective sensing," Elsevier Journal of Computer Vision Image Understate, vol. 100, no.3, pp. 385-415.
[6] KimHon ,Chung(2005),"Electroencephalogram -raphic study of drowsiness in simulated driving with sleep deprivation", International Journal of Industrial Ergonomics., vol. 35, no. 4, pp. 307-320.
[7] K. Harimast (2002)"Human Maehinc. Intedae in an Intelligent vehicle" SAU. vol.56. no.2, pp.4-7.
[8] M. Suzuki, N. Yamamoto, O. Yamamoto, T. Nakano, and S. Yamamoto (2006) "Measurement of Driver's Consciousness by Image Processing- A Method for Presuming Driver's Drowsiness by Eye-Blinks coping with Individual Differences" IEEE International Conference on Systems, Man, and Cybernetics, Taipei, Taiwan. vol. 2, pp. 2891-2896.
[9] Paul Stephen Rau (2005), "Drowsy drivers detection and warning system for commercial vehicle drivers: Field proportional test design, analysis, and progress", Proc. - 19th International Technical Conference on the Enhanced Safety of Vehicles, Washington, D.C.,
[10] Perez, Claudio A. et al., (2001). "Face and Eye Tracking Algorithm Based on Digital Image Processing", IEEE System, Man and Cybernetics 2001 Conference, vol. 2, pp1178-1188.
[11] P. P. Caffier, U. Erdmann, and P. Ullsperger, (2003) "Experimental evaluation of eye-blink parameters as a Drowsiness measure", Eur. Journal of Applied Physiology, vol.89, no.3-4, pp.319-325.
[12] S. Singh. and N. P. Fapanikolopaulas (1999), "Monitoring Driver Fatigue Using Facial Analysis Technologies", IEEE International conference on the Intelligent Transportation Systems. pp.316-318.