Abstract
There are 1.24 million traffic accidents every year with 2.4% caused by drowsy drivers. In that context, several methods for drowsiness detection have been developed. Nevertheless, despite the huge amount of researches, the several devices on markets, and car systems; it is not clear which method is the most appropriate, what sensors are the most useful and least intrusive. This study, shows a systematic literature review of the most recently and relevant methods.
| Original language | English |
|---|---|
| Pages (from-to) | 152-161 |
| Number of pages | 10 |
| Journal | CEUR Workshop Proceedings |
| Volume | 2747 |
| State | Published - 2020 |
| Externally published | Yes |
| Event | 6th Iberoamerican Conference of Computer Human Interaction, HCI 2020 - Arequipa, Peru Duration: 16 Sep 2020 → 18 Sep 2020 |
Bibliographical note
Funding Information:? Supported by INNOVATE-PER?, Universidad la Salle and X-traplus.
Publisher Copyright:
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Keywords
- Drowsiness Detection
- Fatigue Detection
- Survey