Multimodal features for detection of driver stress and fatigue: review
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F20%3A73600827" target="_blank" >RIV/61989592:15210/20:73600827 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26220/20:PU135930
Result on the web
<a href="https://ieeexplore.ieee.org/document/9031734/media#media" target="_blank" >https://ieeexplore.ieee.org/document/9031734/media#media</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TITS.2020.2977762" target="_blank" >10.1109/TITS.2020.2977762</a>
Alternative languages
Result language
angličtina
Original language name
Multimodal features for detection of driver stress and fatigue: review
Original language description
Driver fatigue and stress significantly contribute to higher number of car accidents worldwide. Although, different detection approaches have been already commercialized and used by car producers (and third party companies), research activities in this field are still needed in order to increase the reliability of these alert systems. Also, in the context of automated driving, the driver mental state assessment will be an important part of cars in future. This paper presents state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation. We describe in details various signals (biological, car and video) and derived features used for these tasks and we discuss their relevance and advantages. In order to make this review complete, we also describe different datasets, acquisition systems and experiment scenarios.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20202 - Communication engineering and systems
Result continuities
Project
<a href="/en/project/TL01000216" target="_blank" >TL01000216: Complex physiological monitoring of the driver with respect to psychological factors affecting driving behavior</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
ISSN
1524-9050
e-ISSN
—
Volume of the periodical
2020
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
20
Pages from-to
1-20
UT code for WoS article
000658360600001
EID of the result in the Scopus database
2-s2.0-85107408203