Driver fatigue resulting from sleep deprivation or sleep disorders is an important factor in the creasing number of accidents on today's roads. In this paper, we describe a real-time online safety prototype that controls the vehicle speed under driver fatigue. The purpose of such a model is to advance a system to detect fatigue symptoms in drivers and control the speed of vehicle to avoid accidents. The main components of the system consists of a small camera for real-time driver’s image acquisition, a nonlinear eye tracking algorithm based on Unscented Kalman Filter for driver fatigue detection, and an adaptive speed controller designed using the theory of sliding mode servo control for providing precise positioning of the throttle valve to control speed of vehicle. This system was tested adequately in a realistic driving environment with subjects of different genders, with/without glasses, day/night driving, commercial/non-commercial drivers, continuous driving time, and under different road conditions. The last experimental results show the validity of the proposed model for vehicle speed controller based on driver fatigue detection.

Fatigue detection , Sliding mode servo control, Electronic Throttle Control