IDENTIFICATION OF DRIVER'S DROWSINESS USING DRIVING INFORMATION AND EEG

The paper summarizes the first results of an identification of sleepy state of drivers using a complex set of outputs from simulated driving. The driving information, such as deviation from the centerline of the road and the steering wheel position as well as two-point EEG, was used. The process consists of the preprocessing of data, in fact a transformation into a form proper for classification, and a classification into one of two classes, i.e. wakefulness and drowsiness. There were two groups of drivers submitted to tests, the wakeful ones, and the drivers after serious sleep deprivation. We found that it is possible to distinguish these groups using an appropriate classifier with some rather substantial error, which can possibly be tackled by using an apt methodology.