Due to a reduction in reaction time and, consequently, the driver’s concentration, driving when fatigued has become an issue throughout time. Consequently, likelihood of having accident and it being fatal increases. In this work, we aim identify automatic method capable detecting drowsiness transitions by considering time, frequency, nonlinear domains heart rate variability. Therefore, methodol...

The primary reason for road accidents is drowsiness reported by National Highway Traffic Safety Administration (NHTSA). To overcome this issue, researchers have proposed and implemented various methods based on driver behaviour vehicle movements. Vehicle-based often rely a set of predetermined parameters to detect drowsiness, such as changes in steering wheel angle or lane deviation. However, t...

Traffic accidents due to human errors cause many deaths and injuries around the world. To help in reducing this fatality, in this research, a new module for Advanced Driver Assistance System (ADAS) for automatic driver drowsiness detection based on visual information and Artificial Intelligence is presented. The aim of this system is to locate, to track and to analyze the face and the eyes to c...

Drivers who do not take regular breaks when driving long distances run a high risk of becoming drowsy a state which they often fail to recognize early enough according to the experts. Studies show that around one quarter of all serious motorway accidents are attributable to sleepy drivers in need of a rest, meaning that drowsiness causes more road accidents than drink-driving. Attention assist ...