Incorporation of Eye Movement in Vehicle Dynamics and Auto Notification System

  • Authors

    • S. Venkatraman
    • C. Balamurugan
    • E. Karthikeyan
    • V. Kishore
    • R. Hariharan
    https://doi.org/10.14419/ijet.v7i4.6.28930
  • .

  • Here vision based gradient derivative model is proposed to detect eye blink for fully automated vehicle control system. In addition, the proposed model also integrates tiny encrypted IR based codebook model for sending notifications to other vehicles in order to remotely forward their status. This system comprised of a simple pre-processing and feature extraction methods and requires no human intervention to reduce the false rate. It allows for prompt accessibility, efficient usage of vision input characteristics and provides user convenience. The aim of the work presented in this thesis is to make automatic vehicle control system and IR based signal reception codec to combat environmental differences

  • References

    1. [1] P. S. Rau, “Drowsy Driver Detection and Warning System for Commercial Vehicle Drivers: Field Operational Test Design, Data Analysis, and Progress,†Nat. Highway Traffic Safety Admin., US, 05-0192, Apr. 2016.

      [2] C. Zhao, C. Zheng, M. Zhao, J. Liu and Y. Tu. (2016, Mar.). Automatic classification of driving mental fatigue with EEG by wavelet packet energy and KPCA-SVM. Int. J. of Innov. Comput. and Control. [Online]. 7(3), pp. 1157-1168. Available: http://www.ijicic.org/09-1175-1.pdf

      [3] D. McDonald, C. Schwarz, J. D. Lee and T. L. Brown. (2017, Sept.). Real-time detection of drowsiness related lane departures using steering wheel angle. Proc. Of the Human Factors and Ergonomics Society 56th Annual Meeting 2012. [Online]. 56(1), pp. 2201-2205. Available: http://pro.sagepub.com/content/56/1/2201.full.pdf

      [4] J. Krajewski, and D. Sommer, “Steering wheel behavior based estimation of fatigue,†in Proc. Of Fifth Int. Driving Symp. On Human Factors in Driver Assessment, Training and Vehicle Design, Germany, 22-25 June 2017, pp. 118-124.

      [5] D. J. King, D. K. Mumford, and G. P. Siegmund, “An algorithm for detecting heavy-truck driver fatigue from steering wheel motion,†in Proc. of 16th Int. Tech. Conf. on the Enhanced Safety of Vehicles, Held Windsor, Ontario, Canada, 31 May – 4 June 2018, pp. 873-882.

      [6] C. Cao, Y. Weng, S. Zhou, Y. Tong, and K. Zhou, “Facewarehouse: A 3D facial expression database for visual computing,†IEEE Trans. Vis. Comput. Graphics, vol. 20, no. 3, pp. 413–425, Mar. 2014.

      [7] C. Ahlstrom, K. Kircher, and A. Kircher, “A gaze-based driver distraction warning system and its effect on visual behavior,†IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, pp. 965–973, Jun. 2013..

      [8] F. Yang, E. Shechtman, J.Wang, L. Bourdev, and D. Metaxas, “Face morphing using 3D-aware appearance optimization,†in Proc. Graph. Interace Conf. Can. Inf. Process. Soc., 2012, pp. 93–99.

      [9] Y. Dong, Z. Hu, K. Uchimura, and N. Murayama, “Driver inattention monitoring system for intelligent vehicles: A review,†IEEE Trans. Intell. Transp. Syst., vol. 12, no. 2, pp. 596–614, Jun. 2011. 5. D. WHansen and Q. Ji, “In the eye of the beholder: A survey of models for eyes and gaze,†IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 3, pp. 478–500, Mar. 2010.

      [10] P. S. Rau, “Drowsy Driver Detection and Warning System for Commercial Vehicle Drivers: Field Operational Test Design, Data Analysis, and Progress,†Nat. Highway Traffic Safety Admin., US, 05-0192, Apr. 2005.

      [11] C. Zhao, C. Zheng, M. Zhao, J. Liu and Y. Tu. (2011, Mar.). Automatic classification of driving mental fatigue with EEG by wavelet packet energy and KPCA-SVM. Int. J. of Innov. Comput. and Control. [Online]. 7(3), pp. 1157-1168.

      [12] D. McDonald, C. Schwarz, J. D. Lee and T. L. Brown. (2012, Sept.). Real-time detection of drowsiness related lane departures using steering wheel angle. Proc. Of the Human Factors and Ergonomics Society 56th Annual Meeting 2012. [Online]. 56(1), pp. 2201-2205.

      [13] J. Krajewski, and D. Sommer, “Steering wheel behavior based estimation of fatigue,†in Proc. Of Fifth Int. Driving Symp. On Human Factors in Driver Assessment, Training and Vehicle Design, Germany, 22-25 June 2009, pp. 118-124.

      [14] D. J. King, D. K. Mumford, and G. P. Sigmund, “An algorithm for detecting heavy-truck driver fatigue from steering wheel motion,†in Proc. of 16th Int. Tech. Conf. on the Enhanced Safety of Vehicles, Held Windsor, Ontario, Canada, 31 May – 4 June 1998, pp. 873-882.

      [15] Dr. AntoBennet, M, Sankar Babu G, Natarajan S, “Reverse Room Techniques for Irreversible Data Hidingâ€, Journal of Chemical and Pharmaceutical Sciences 08(03): 469-475, September 2015.

      [16] Dr. AntoBennet, M , Sankaranarayanan S, Sankar Babu G, “ Performance & Analysis of Effective Iris Recognition System Using Independent Component Analysisâ€, Journal of Chemical and Pharmaceutical Sciences 08(03): 571-576, August 2015.

      [17] Dr. AntoBennet, M, Suresh R, Mohamed Sulaiman S, “Performance &analysis of automated removal of head movement artifacts in EEG using brain computer interfaceâ€, Journal of Chemical and Pharmaceutical Research 07(08): 291-299, August 2015.

      [18] .Dr. AntoBennet, M “A Novel Effective Refined Histogram For Supervised Texure Classificationâ€, International Journal of Computer & Modern Technology , Issue 01 ,Volume02 ,pp 67-73, June 2015.

      [19] Dr. AntoBennet, M, Srinath R,Raisha Banu A,“Development of Deblocking Architectures for block artifact reduction in videosâ€, International Journal of Applied Engineering Research,Volume 10, Number 09 (2015) pp. 6985-6991, April 2015.

      [20] AntoBennet, M & JacobRaglend, “Performance Analysis Of Filtering Schedule Using Deblocking Filter For The Reduction Of Block Artifacts From MPEQ Compressed Document Imagesâ€, Journal of Computer Science, vol. 8, no. 9, pp. 1447-1454, 2012.

      [21] AntoBennet, M & JacobRaglend, “Performance Analysis of Block Artifact Reduction Scheme Using Pseudo Random Noise Mask Filteringâ€, European Journal of Scientific Research, vol. 66 no.1, pp.120-129, 2011.

  • Downloads

  • How to Cite

    Venkatraman, S., Balamurugan, C., Karthikeyan, E., Kishore, V., & Hariharan, R. (2018). Incorporation of Eye Movement in Vehicle Dynamics and Auto Notification System. International Journal of Engineering & Technology, 7(4.6), 563-566. https://doi.org/10.14419/ijet.v7i4.6.28930