Accident Avoidance and Detection on Highways

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2012 by IJETT Journal
Volume-3 Issue-2                          
Year of Publication : 2012
Authors :  S.P. Bhumkar, V.V. Deotare, R.V.Babar


S.P. Bhumkar, V.V. Deotare, R.V.Babar. " Accident Avoidance and Detection on Highways". International Journal of Engineering Trends and Technology (IJETT). V3(2):247-252 Mar-Apr 2012. ISSN:2231-5381. published by seventh sense research group


Technological approaches for detecting and monitoring fatigue levels of driver fatigue continue to emerge and many are now in the development, validation testing, or early implementation stages. Previous studies have review ed available fatigue detection and prediction technologies and methodologies. As the name indicates t his project is about advanced technologies in cars for making it m ore intelligent and interactive for avoiding accidents on roads. By using ARM7 this syste m becomes more efficient, reliable & effective. There are very less number of systems implemented on human behaviour detection in or with cars. In this paper, we describe a real - time online safety prototype that controls the vehicle speed under driver fati gue. The purpose of such a model is to advance a system to detect fatigue symptoms in drivers and control the speed of vehicle to avoid accidents. The main components of the system consist of number of real time sensors like gas, eye blink, alcohol, fuel, impact sensors and a software interface with GPS and Google Maps APIs for location


[1] Zutao Zhang, Jiashu Zhan g , “A Novel Vehicle Safety Model: Vehicle speed Controller under Driver Fatigue”, “IJCSNS International Journal of Computer Science and Network Security”, VOL.9 No.1, January 2009
[2] M. Bertozzi, A. Broggi, M. Cellario, A. Fascioli, P. Lombardi, and M.Por ta, “Artifical vision in road vehicles,” Proceedings of the IEEE , vol. 90,no. 7, pp. 1258 – 1271, 2002.
[3] S. Tsugawa and Sadayuki, “Vision - based vehicle on japan: Machine vision systems and driving control systems,” IEEE Trans. on Ind. El.??? , vol. 41, no. 4, pp. 398 – 405, 1994.
[4] Vehicle - highway automation activities in the United States . U.S. Dept of Transportation, 1997.
[5] C. Thorpe, J.D. Carlson, D. Duggins, J. Gowdy, R. MacLachlan, C. Mertz, A. Suppe, and C. Wan, “Safe robot driving in cluttered env ironments,” 11th International Symposium of Robotics Research , 2003.
[6] Qian Martin Eriksson, Nikolaos P. Papanikolopoulos, Eye - Tracking for Detection of Driver fatigue. Proceedings of the international Conference on intelligent Transportation System, Bos ton, MA, November 1997, pp.314 - 319.
[7] Qiang Ji, Zhiwei Zhu, and Peilin Lan, Real - Time Nonintrusive Monitoring and Prediction of Driver Fatigue. IEEE Transactions on Vehicular Technology, VOL. 53, NO. 4, July 2004, pp.1052 - 1068.

GPS Receiver, ARM, Sensors