Eye tracking based driver fatigue monitoring and warning system

The main idea behind this project is to develop a non-intrusive system which can detect fatigue of the driver and issue a timely warning. Since a large number of road accidents occur due to the driver drowsiness. Hence this system will be helpful in preventing many accidents, and consequently save money and reduce personal suffering. This system will monitor the driver's eyes using camera and by developing an algorithm we can detect symptoms of driver fatigue early enough to avoid accident. So this project will be helpful in detecting driver fatigue in advance and will gave warning output inform of sound and seat belt vibration whose frequency will vary between 100 to 300 Hzs. Moreover the warning will be deactivated manually rather than automatically. So for this purpose a deactivation switch will be used to deactivate warning. Moreover if driver felt drowsy there is possibility of sudden acceleration or deacceleration hence we can judge this by Plotting a graph in time domain and when all the three input variables shows a possibility of fatigue at one moment then a Warning signal is given in form of text or red colour circle. This will directly give an indication of drowsiness/fatigue which can be further used as record of driver performance.

[1]  Wang Jian,et al.  Design and Simulated Implementation of MATLAB-Based Warning System for Fatigue Driving Driver , 2009, 2009 Ninth International Conference on Hybrid Intelligent Systems.

[2]  M Kutila.  Methods for machine vision based driver monitoring applications , 2006 .

[3]  Mohamad Hoseyn Sigari.  Driver Hypo-vigilance Detection Based on Eyelid Behavior , 2009, 2009 Seventh International Conference on Advances in Pattern Recognition.

[4]  C D Wylie,et al.  COMMERCIAL MOTOR VEHICLE DRIVER FATIGUE AND ALERTNESS STUDY: PROJECT REPORT , 1996 .

[5]  R J Fairbanks,et al.  RESEARCH ON VEHICLE-BASED DRIVER STATUS/PERFORMANCE MONITORING; DEVELOPMENT, VALIDATION, AND REFINEMENT OF ALGORITHMS FOR DETECTION OF DRIVER DROWSINESS. FINAL REPORT , 1994 .

[6]  Hyeran Byun,et al.  Efficient Measurement of Eye Blinking under Various Illumination Conditions for Drowsiness Detection Systems , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[7]  Thomas A. Dingus,et al.  IN-VEHICLE INFORMATION SYSTEMS BEHAVIORAL MODEL AND DESIGN SUPPORT: FINAL REPORT , 2000 .

[8]  B. Carnahan,et al.  A drowsy driver detection system for heavy vehicles , 1998, 17th DASC. AIAA/IEEE/SAE. Digital Avionics Systems Conference. Proceedings (Cat. No.98CH36267).

[9]  Carryl L. Baldwin,et al.  Driver fatigue: The importance of identifying causal factors of fatigue when considering detection and countermeasure technologies , 2009 .

[10]  Lei Yunqi,et al.  Recognition of Eye States in Real Time Video , 2009, 2009 International Conference on Computer Engineering and Technology.

[11]  Luis Miguel Bergasa,et al.  Driver fatigue detection system , 2009, 2008 IEEE International Conference on Robotics and Biomimetics.

[12]  R P Hamlin.  THREE-IN-ONE VEHICLE OPERATOR SENSOR , 1995 .

[13]  Weixing Wang,et al.  Driver Fatigue Detection Based on Eye Tracking , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[14]  Preeti R. Bajaj,et al.  Driver Fatigue Detection Based on Eye Tracking , 2008, 2008 First International Conference on Emerging Trends in Engineering and Technology.

[15]  Tiziana D'Orazio,et al.  An algorithm for real time eye detection in face images , 2004, ICPR 2004.

[16]  Jesper Sandin,et al.  Vehicle control and drowsiness , 2002 .

[17]  Riza Atiq Abdullah O.K. Rahmat,et al.  Intelligent transport system for motorcycle safety and issues , 2009 .

[18]  Jane C. Stutts,et al.  WHY DO PEOPLE HAVE DROWSY DRIVING CRASHES? INPUT FROM DRIVERS WHO JUST DID , 1999 .

[19]  Marie-Pierre Bruyas,et al.  Simultaneous interaction with in-vehicle systems while turning left: comparison among three groups of drivers , 2009 .

[20]  Changle Zhou,et al.  Real-Time Eye Detection in Video Streams , 2008, 2008 Fourth International Conference on Natural Computation.

[21]  Yang Jie,et al.  Real-time detecting system of the driver's fatigue , 2006, 2006 Digest of Technical Papers International Conference on Consumer Electronics.

[22]  Qiang Ji,et al.  Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance , 2002, Real Time Imaging.