Drowsy driving has a high potential for causing serious accidents because it leads to collisions without hazard avoidance. Against this backdrop, in Europe, the installation of driver drowsiness and attention warning (DDAW) systems became mandatory under the General Safety Regulations (GSR) in 2022. The DDAW systems use the Karolinska Sleepiness Scale (KSS) to assess the extent of driver drowsiness. However, although various representative indices to quantify drowsiness, such as KSS, are available, they present issues in terms of reproducibility and practical use, and there is currently no uniform index. This present research therefore sought to propose practical new indices of drowsiness. At the same time, this research aims to provide indices based on features extracted from images by focusing on the relationship with the comparatively severe range of drowsiness represented by KSS scores of 7 or higher, which must be detected for compliance with DDAW. The results demonstrated that the occurrence of "Eye closure" and "Yawning" could serve as substitutes for states involving KSS scores of 7 or higher. These drowsiness behaviors can be objectively and reproducibly annotated, leading to the conclusion that they could be candidates for new indicators.
Proposal for Reproducible and Practical Drowsiness Indices
2024 IEEE Intelligent Vehicles Symposium (IV) ; 2983-2988
02.06.2024
1248913 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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