Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existin...

This paper presents a method for detecting vehicles as obstacles in real road scene using a single onboard camera for an automotive vehicle. Vehicles are detected by finding region of interest (boundary detection) using morphological operation in image captured by camera. When a vehicle is found in front of travelled vehicle then the driver assistance system gives warning to the driver to give ...

Driver impairment due to fatigue induced drowsiness is a significant cause of vehicle collisions. One countermeasure that is currently being implemented is Fatigue Warning Systems (FWS) to alert drivers that are drowsy. Behavioural adaptation of drivers to a FWS was evaluated in a closed track study. Thirty-two drivers completed two lengthy overnight drives, separated by one week, with half the...

The article presents a review on vision-based solutions for driver assistance. These solutions support the driver to keep safe travel conditions. They use diverse sensing modalities for the recognition of the environment around the vehicle. Upon detection a critical safety situation they supply the driver with the warning. Four assistance systems have been addressed: TSR Traffic Sign Recognitio...

Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has become an area of substantial research attention in recent years. The present study proposes a method to detect drowsiness in drivers which integrates features of electrocardiography (ECG) and electroencephalography (EEG) to improve detection performance. The study measures differences between the alert ...

This work presents the development of an ADAS (advanced driving assistance system) focused on driver drowsiness detection, whose objective is to alert drivers their drowsy state avoid road traffic accidents. In a environment, it necessary that fatigue detection performed in non-intrusive way, and not bothered with alarms when he or she drowsy. Our approach this open problem uses sequences image...

A monitoring system is designed in where it receives sensory data via wireless sensor network and further processes the data to indicate the current driving aptitude of the driver. Analyzing information related to fatigue using two distinct methods eye movement monitoring and bio signal processing. It is critical that several sensors are integrated and synchronized for a more realistic evaluati...

The main idea behind this project is to develop a system which can detect drowsiness of the driver and giving an indication in the form of alarm. Since a large number of road accidents occur due to the driver drowsiness, here we are proposing a new transportation system which will reduce the accidents. This system will monitor the driver’s eyes using camera and face detection which is very impo...

Unfit drivers are the cause of tens of thousands of incidents on the roadswhich lead to injuries anddeaths. Therefore, it is very important to take preventive measures against such incidents. One of the unfit driving conditions is driving while being drowsy. Using image processing techniques, drowsiness of the driver could be detected and hence such incidents could be prevented. In this work, i...