In order to avoid car crashes, active safety systems are becoming more and more important. Many crashes are caused due to driver drowsiness or mobile phone usage. Detecting the drowsiness of the driver is very important for the safety of a car. Monitoring of vital signs such as respiration rate and heart rate is important to determine the occurrence of driver drowsiness. In this paper, robust v...

Reducing the number of accidents that are caused by drowsiness or fatigue could be achieved by applying different strategies. This paper focuses on the on-line, real time detection of deteriorating driver state and driving behaviour, and on the question what should be done after this has been detected. It reports three studies performed in the TNO driving simulator. The first one leads to the c...

The algorithm based physiological characteristics of driver drowsiness – ocular parameters (derived from the frontal electroencephalogram (EEG)), EEG alpha bursts and spectral power (derived from the central and occipital sites) as well as heart rate variability (HRV) were estimated from data derived during a driving simulator experiment (30 non-professional drivers). The statistical associatio...

Drowsy driving is one of the leading causes traffic accidents all over world. Driving in a monotonous manner for an extended amount time without stopping tiredness and catastrophic accidents. Drowsiness has potential to ruin many people’s lives. As result, real-time system that simple create configure early accurate sleepiness detection required. In this study, vision-based called Driver Detect...

The purpose of this paper is to develop a driver drowsiness and monitoring system that could act as an assistant the during driving process. aimed at reducing fatal crashes caused by driver’s distraction. For drowsiness, operates analysing eye blinks yawn frequency while for distraction, works based on head pose estimation tracking. alarm will be triggered if any these conditions occur. Main pa...