A Survey on Driver Behavior Detection Techniques

Authors

  • Ishita Seth  India

DOI:

https://doi.org//10.32628/IJSRST207384

Keywords:

Automotive, Safety, Active Safety, Passive Safety, terms suggests is for preventing the accidents by providing the warnings or the alerts to the drivers. Head-Up Display, Anti-Lock Braking Systems, Electronic Stability Control, Tire Pressure Monitoring System, Lane Departure Warning System , Adaptive Cruise Control, Driver Monitoring , Blind Spot Detection and Night Vision System.

Abstract

The objective of this paper is to detect the car driver behavior. Many factors can influence the behavior of the driver that includes fatigue, distraction, eye-blinking, taking eyes off from the road, time of the driving etc. The in appropriate behavior while driving the car can leads to accidents that in return damages one

References

  1. "Road Accidents in India" in Government of India Ministry of Road Transport & Highways Transport Research Wing, New Delhi, 2018.
  2. D. Mitrovic, "Reliable Method for Driving Events Recognition", IEEE Trans. In tell. Transport Syst., vol. 6, no. 2, pp. 198-205, 2005.
  3. G. Yang, Y. Lin and P. Bhattacharya, "A driver fatigue recognition model based on information fusion and dynamic Bayesian network", Information Sciences, vol. 180, no. 10, pp. 1942-1954, 2010.
  4. J. C. Stutts, D. W. Reinfurt, L. Staplin and E. A. Rodgman, The role of driver distraction in traffic crashes, 2001.
  5. "Driver fatigue and road accidents: A literature review and position paper", R. Soc. Prevention Accidents, pp. 1-24, Feb. 2001.
  6. D. Mohan, "Analysis of road traffic fatality data for Asia", J. Eastern Asia Soc. Trans. Stud., vol. 9, pp. 1786-1795, 2011.
  7. W. Rongben, G. Lie, T. Bingliang and J. Lisheng, "Monitoring Mouth Movement for Driver Fatigue or Distraction with One Camera", 7th International IEEE Conference on Intelligent Transportation Systems, pp. 314-319, 2004.
  8. M.S. Devi and PR. Bajaj, "Driver Fatigue Detection Based on Eye Tracking", IEEE First InternationalConference on Emerging Trends in Engineering and Technology, pp. 649-652, 2008.
  9. T. Bär, D. Nienhüser, R. Kohlhaas and J.M. Zöllner, "Probabilistic Driving Style Determination by means of a Situation Based Analysis of the Vehicle Data", 14th International IEEE Conference on Intelligent Transportation Systems, pp. 1698-1703, 2011.
  10. J. Dai, J. Teng, X. Bai, Z. Shen and D. Xuan, "Mobile phone based drunk driving detection", 4th InternationalConference on Pervasive Computing Technologies for Healthcare, pp. 1-8, 2010.
  11. M. Fazeen, B. Gozick, R. Dantu, M. Bhukhiya and M. González, "Safe Driving Using Mobile Phones", IEEE Trans. In tell. Transport Syst., vol. 13, no. 3, pp. 1462-1468, 2012.
  12. Tomer Toledo and Tsippy Lotan, "In-Vehicle Data Recorder for Evaluation of Driving Behavior and Safety" in Transportation Research Board of the National Academies, Washington, D.C, 2006.
  13. L. Zhang, J. Wang, F. Yang and K. Li, "A quantification method of driver characteristics based on Driver Behavior Questionnaire," 2009 IEEE Intelligent Vehicles Symposium, Xi'an, 2009, pp. 616-620, doi: 10.1109/IVS.2009.5164348.

International Journal of Scientific Research in Science and Technology

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Published

2020-06-30

Issue

Volume 7, Issue 3, May-June-2020

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Ishita Seth, " A Survey on Driver Behavior Detection Techniques, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 7, Issue 3, pp.401-404, May-June-2020. Available at doi : https://doi.org/10.32628/IJSRST207384