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dc.contributor.authorYUZOFF, Norhasliza M.
dc.contributor.author
 hal.structure.identifier
AHMAD, Rana Fayyaz
303395 Universiti Teknologi Malaysia [UTM]
dc.contributor.authorGUILLET, Christophe
dc.contributor.author
 hal.structure.identifier
MALIK, Aamir Saeed
303395 Universiti Teknologi Malaysia [UTM]
dc.contributor.author
 hal.structure.identifier
SAAD, Naufal M.
303395 Universiti Teknologi Malaysia [UTM]
dc.contributor.author
 hal.structure.identifier
MERIENNE, Frédéric
495876 Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] [Le2i]
dc.date.accessioned2018
dc.date.available2018
dc.date.issued2017
dc.date.submitted2018
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/10985/12654
dc.description.abstractDriving distraction is a topic of great interest in the transport safety-research community, because it is now a primary cause of road accidents. A recent report has revealed that distraction is more alarming than previously thought, and a suitable measurement to effectively detect distraction is required. Most agree that driving distraction actually comprises the simultaneous interaction of two or more types of distraction. The purpose of this paper is, therefore, to determine the promising method for measuring visual cognitive distraction. We discuss the five common measurement methods for visual and cognitive driving distraction, which include driving performance, driver physical measures, driver biological measures, subjective reports, and hybrid measures. Hybrid measurement of driver's physical measures (e.g., eye movement) and driver's biological measures (e.g., electroencephalogram) is better than other methods at detecting types of visual cognitive distraction. This new perspective on measurement methods will help the field of transport safety to determine the best means of detecting and measuring the effect of visual cognitive distraction.
dc.language.isoen
dc.publisherIEEE
dc.rightsPost-print
dc.subjectDriving distraction
dc.subjectCognition
dc.subjectVisual
dc.subjectDetection
dc.titleSelection of Measurement Method for Detection of Driver Visual Cognitive Distraction: A Review
dc.identifier.doi10.1109/ACCESS.2017.2750743
dc.typdocArticle dans une revue avec comité de lecture
dc.localisationInstitut de Chalon sur Saône
dc.subject.halInformatique: Interface homme-machine
dc.subject.halInformatique: Synthèse d'image et réalité virtuelle
dc.subject.halSciences de l'ingénieur: Traitement du signal et de l'image
ensam.audienceInternationale
ensam.page22844-22854
ensam.journalIEEE Access
ensam.volume5
ensam.peerReviewingOui
hal.identifierhal-01712800
hal.version1
hal.submission.permittedupdateMetadata
hal.statusaccept
dc.identifier.eissn2169-3536


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