Detection and prediction of driver drowsiness using artificial neural network models-Reference-Cited by-同舟云学术

Detection and prediction of driver drowsiness using artificial neural network models

Published:2019-05 Issue: Volume:126 Page:95-104
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Jacobé de Naurois Charlotte,Bourdin Christophe,Stratulat Anca,Diaz Emmanuelle,Vercher Jean-Louis

Funder

PSA Group via the OpenLab agreement with Aix-Marseille University and CNRS entitled “Automotive Motion Lab”

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference81 articles.

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2. Countermeasures for Fatigue in Transportation: a Review of Existing Methods for Drivers on Road, Rail, Sea and in Aviation. Statens väg- Och Transportforskningsinstitut;Anund,2015

3. A psychophysiological investigation of the effects of driving longer-combination vehicles;Apparies;Ergonomics,1998

4. How do prolonged wakefulness and alcohol compare in the decrements they produce on a simulated driving task?;Arnedt;Accid. Anal. Prev.,2001

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