It is inevitable for driver assist and warning systems to consider the drivers' state of consciousness. Drowsiness is one of the important factors in estimating the drivers' state of consciousness. A Method to extract the driver's initial stage of drowsiness was developed by means of the eyelid's opening relevant to each various characteristic of objects with motion pictures processing in the actual driving environment. The result was that an increase of the long eyelid closure time was the key factor in estimating the initial stage of drivers' drowsiness while driving. And the state of drowsiness could be presumed by checking the frequencies of long eyelid closure time per unit period.

There is no clear criterion yet for evaluating wipers based on performances of wiping raindrops and visibility in forward view. In the visibility evaluation in rainy driving, it is important to examine spatial frequency and contrast of objects in forward view. Spatial frequency and contrast of image which were affected by raindrops are calculated based on them of background board which were printed stripe patterns. Variations with time of power of analysed frequency and decreased contrast are synchronized with motion of the wiper for the all experimental cases. Moreover, we executed questionnaire, and evaluated the view of the background board. These results show that the proposed methods have been validated in evaluation with wiping performance.