Driving security is an important task for human society. The major challenge in the field of accident avoidance systems is the driver vigilance monitoring. The lack of vigilance can be noticed by various ways, such as, fatigue, drowsiness and distraction. Hence, the need of a reliable driver’s vigilance decrease detection system which can alert drivers before a mishap happens. In this paper, we present a novel approach for vigilance estimation based on multilevel system by combining head movement analysis and eyes blinking. We have used Viola and Jones algorithm to analyse head movement and a classification system using wavelet networks for eyelid closure measuring. The contribution of our application is classifiying the vigilance state at multi level. This is different from the binary-class (awakening or hypovigilant state) existing in most popular systems.