Uppiggande effekter av sömnskattningar: Hur påverkar det GSR och förarövervakning?
DOI: 10.65151/vti507982
archive: archived pipeline: cataloged verified
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Summary
This study investigates whether the act of rating one’s sleepiness using the Karolinska Sleepiness Scale (KSS) induces a temporary alerting effect that distorts physiological and behavioral measurements. This research is motivated by the critical role KSS plays as the reference standard (“ground truth”) for developing and type-approving Driver Drowsiness and Attention Warning (DDAW) systems under the EU’s General Safety Regulation (GSR). If the rating process itself alters the driver’s state, it could compromise the validity of data used to train detection algorithms, potentially leading to unreliable systems and increased fatigue-related crashes. The researchers analyzed data from five driving simulator studies involving 84 participants and 2,701 KSS ratings. Participants drove during the day and at night after sleep restriction, providing KSS ratings every five minutes. The study tracked eye movements (blink duration and eyelid closure speed), heart rate, brain activity (EEG alpha and theta waves), and lateral lane position deviation (SDLP). Linear regression models with three segments were applied to time-series data surrounding each rating to quantify the immediate impulse and the duration ($\tau$) of any alerting effect. The analysis also explored differences between verbal and tablet-based rating modalities. Results indicate that KSS ratings trigger a transient alerting effect, particularly at high sleepiness levels (KSS 7–9). Physiological indicators responded quickly, with EEG changes fading within 30–40 seconds and eye/heart rate changes dissipating within 52–78 seconds. In contrast, driving behavior (SDLP) was influenced for a longer period, up to approximately 115 seconds. Exploratory findings suggested that tablet-based ratings produced a shorter alerting effect than verbal ratings, though this comparison was limited by non-randomized modalities across participants. The study concludes that data collected immediately after a KSS rating should be excluded when training and validating drowsiness detection algorithms to prevent distortion. Specifically, the authors recommend excluding data within ~60 seconds for physiological features and up to ~120 seconds for behavioral metrics. Standardizing the self-rating procedure and excluding this “alerting window” will improve the reliability of DDAW systems, reduce false alarms, and enhance traffic safety. Future research should address the limitations of simulator-only data and further investigate the impact of rating modalities using within-subject designs.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-19 |
| archive | success | canonical_url | — | — | 1 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-19 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | partial | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified_with_issues.
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- Empirical Findings: physiological data
- Methodological Resource: validation psychometrics