05 mai 2020

Renault R-NEST: using stimulation to fight hypovigilance at the wheel

Renault R-NEST: using stimulation to fight hypovigilance at the wheel The Renault R-NEST project (Renault Research Tool for NEuroscience STudies) was developed by the Groupe Renault Research department as a neurophysiology research tool and demo model for these types of system. The purpose of this research is to help reduce accidents caused by driving fatigue. The demo model consists of a static driving module. It has two cameras (3D and 2D) that capture and record driver reactions and measure a large amount of data (heart rate,... [Lire la suite]
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04 mai 2020

Snooze mobiles: how vibrations in cars make drivers sleepy

Snooze mobiles: how vibrations in cars make drivers sleepy New research has found the natural vibrations of cars make people sleepier, affecting concentration and alertness levels just 15 minutes after drivers get behind the wheel. With about 20 per cent of fatal road crashes involving driver fatigue, RMIT University researchers hope their findings can be used by manufacturers to improve car seat designs to help keep drivers awake. Professor Stephen Robinson said the effects of physical vibration on drivers were not... [Lire la suite]
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21 janvier 2018

Tech Developed to Prevent Drowsy Driving

Tech Developed to Prevent Drowsy Driving Automotive supplier Hyundai Mobis has unveiled technology designed to detect when a driver is dozing off and leaving the road, so vehicle control can be transitioned to autonomous driving mode and the car can be pulled over safely and stopped. The company showcased its latest DDREM (Departed Driver Rescue and Exit Maneuver) technology at the Consumer Electronics Show last week. By focusing only on the safety benefits of autonomous driving, DDREM technology will bring such advantages to... [Lire la suite]
16 mars 2017

A Driver Face Monitoring System for Fatigue and Distraction Detection

A Driver Face Monitoring System for Fatigue and Distraction Detection Driver face monitoring system is a real-time system that can detect driver fatigue and distraction using machine vision approaches. In this paper, a new approach is introduced for driver hypovigilance (fatigue and distraction) detection based on the symptoms related to face and eye regions. In this method, face template matching and horizontal projection of top-half segment of face image are used to extract hypovigilance symptoms from face and eye, respectively.... [Lire la suite]
29 juillet 2016

Physiological signal based detection of driver hypovigilance using higher order spectra

Physiological signal based detection of driver hypovigilance using higher order spectra In this work, the focus is on developing a system that can detect hypovigilance, which includes both drowsiness and inattention, using Electrocardiogram (ECG) and Electromyogram (EMG) signals. Drowsiness has been manipulated by allowing the driver to drive monotonously at a limited speed for long hours and inattention was manipulated by asking the driver to respond to phone calls and short messaging services. ECG and EMG signals along with the... [Lire la suite]
29 février 2016

Capturing the advanced driver-assistance systems opportunity

Capturing the advanced driver-assistance systems opportunity (McKinsey report) New automotive active-safety systems could provide a route to autonomous cars. Yet the auto industry has work to do to convert consumer interest in these features into actual adoptions. While the prospect of completely autonomous, driverless cars continues to grab headlines globally, a quiet revolution is already fundamentally altering our vehicles. The availability and sophistication of new automotive-safety systems, collectively known as advanced... [Lire la suite]
18 novembre 2014

Fatigue sensor: When EPFL innovates

Fatigue and drowsy driving are often the cause of accidents of traffic. Several drowsiness detection systems already been tested in practice. EPFL innovates in this area: a student recently proposed a fatigue detection algorithm based on video the analysis of eye closure. A prototype will be tested in terms actual driving. La fatigue et la somnolence au volant sont bien souvent à l’origine d’accidents de la circulation. Plusieurs systèmes de détection de la somnolence ont déjà été testés dans la pratique. L’EPFL innove dans ce... [Lire la suite]