Fatigue is one of the most pervasive yet under-investigated causes of human-error-related driving accidents, incidents, and injuries. Several studies suggest that 25-30% of driving accidents are fatigue related (Horne et al., 1995). However, government reports estimate that only 1-4% of crashes may be attributable to the driver falling asleep or being drowsy, based largely on data derived from ...

The large number of automobile accidents due to driver drowsiness is a critical concern of many countries. To solve this problem, numerous methods of countermeasure have been proposed. However, the results were unsatisfactory due to inadequate accuracy of drowsiness detection. In this study, we introduce a new approach, a combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG a...

The aim of this study was to explore the effectiveness of behavioral evaluation measures for predicting drivers’ subjective drowsiness. Behavioral measures included neck vending angle (horizontal and vertical), back pressure, foot pressure, COP (Center of Pressure) movement on sitting surface, and tracking error in driving simulator task. Drowsy states were predicted by means of the multinomial...

The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to data-mi...

This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn)featuresfromfixedslidingwindowsonreal-timesteeringwheelanglestimeseries. Afterthat, this system linearizes t...

Recently, the upsurge in accidents is caused due to driver drowsiness arises lack of sleep, fatigue and other health factors. The leads mortality, loss properties serious conditions. Hence, it necessary prevent by drivers. At present, automated model effective for detection recognition. In this research paper, developed a MCNN (Multi-Scale Convolutional Neural Network) framework classification ...

Driving is a complicated process that demands coordination between range of neurocognitive functions, including attention, visuo-perception, and appropriate judgment, as well sensory motor responses. Therefore, several factors may reduce the driving performance an individual, such sleepiness, distraction, overspeeding, alcohol consumption, sedative drugs, all which increase hazard vehicle accid...

BACKGROUND Sleepiness may account for up to 20% of crashes on monotonous roads, especially highways. Obstructive sleep apnea (OSA) is the most common medical disorder that causes excessive daytime sleepiness, increasing the risk for drowsy driving two to three times. The purpose of these guidelines is to update the 1994 American Thoracic Society Statement that described the relationships among ...