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  4. Classification of driver fatigue in conditionally automated driving using physiological signals and machine learning
 

Classification of driver fatigue in conditionally automated driving using physiological signals and machine learning

URI
https://arbor.bfh.ch/handle/arbor/37217
Version
Published
Date Issued
2024-07
Author(s)
Meteier, Quentin
Favre, Renée  
Viola, Sofia
Capallera, Marine
Angelini, Leonardo
Mugellini, Elena
Sonderegger, Andreas  
Type
Article
Language
English
Subjects

Driver state Driving ...

Subjects
BF Psychology
HE Transportation and Communications
DOI
10.24451/arbor.22160
https://doi.org/10.24451/arbor.22160
Publisher DOI
10.1016/j.trip.2024.101148
Journal
Transportation Research Interdisciplinary Perspectives
ISSN
25901982
Publisher URL
https://www.sciencedirect.com/science/article/pii/S2590198224001349
Related URL
https://www.sciencedirect.com/journal/transportation-research-interdisciplinary-perspectives
Organization
Institut New Work (INW)  
Neue Arbeits- und Organisationsformen  
Wirtschaft  
Volume
26
Publisher
Elsevier
Submitter
Sonderegger, Andreas
Citation apa
Meteier, Q., Favre, R., Viola, S., Capallera, M., Angelini, L., Mugellini, E., & Sonderegger, A. (2024). Classification of driver fatigue in conditionally automated driving using physiological signals and machine learning. In Transportation Research Interdisciplinary Perspectives (Vol. 26). Elsevier. https://doi.org/10.24451/arbor.22160
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open access

Name

Meteier_2024_Driver fatigue.pdf

License
Attribution 4.0 International
Version
published
Size

3.77 MB

Format

Adobe PDF

Checksum (MD5)

2de92175ba041bd2231e086eb81749f8

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