Title :
Camera-based drowsiness reference for driver state classification under real driving conditions
Author :
Friedrichs, Fabian ; Yang, Bin
Author_Institution :
Syst. Theor. & Signal Process., Univ. of Stuttgart, Stuttgart, Germany
Abstract :
Experts assume that accidents caused by drowsiness are significantly under-reported in police crash investigations (1-3%). They estimate that about 24-33% of the severe accidents are related to drowsiness. In order to develop warning systems that detect reduced vigilance based on the driving behavior, a reliable and accurate drowsiness reference is needed. Studies have shown that measures of the driver´s eyes are capable to detect drowsiness under simulator or experiment conditions. In this study, the performance of the latest eye tracking based in-vehicle fatigue prediction measures are evaluated. These measures are assessed statistically and by a classification method based on a large dataset of 90 hours of real road drives. The results show that eye-tracking drowsiness detection works well for some drivers as long as the blinks detection works properly. Even with some proposed improvements, however, there are still problems with bad light conditions and for persons wearing glasses. As a summary, the camera based sleepiness measures provide a valuable contribution for a drowsiness reference, but are not reliable enough to be the only reference.
Keywords :
accident prevention; alarm systems; behavioural sciences; cameras; image classification; road safety; sleep; statistical analysis; traffic engineering computing; camera based sleepiness measurement; camera-based drowsiness reference; classification method; driver state classification; drivers eyes; eye tracking; in-vehicle fatigue prediction measurement; police crash investigations; real driving conditions; statistical analysis; warning systems; Accidents; Cameras; Computer crashes; Electroencephalography; Electrooculography; Fatigue; Intelligent vehicles; Roads; Signal processing; US Department of Transportation; KSS; blinking behavior; classification; driver monitoring; drowsiness detection; eye-tracking;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2010 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-7866-8
DOI :
10.1109/IVS.2010.5548039