A gaze-based driver distraction countermeasure: Comparing effects of multimodal alerts on driver's behavior and visual attention
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study, introduces and evaluates different countermeasures using real-time eye-tracking data. The countermeasures detect when driver gaze deviates from the road for longer than a predetermined threshold and then redirect the driver's attention back to the road. The countermeasures include bimodal and trimodal alerts using combinations of auditory, tactile, and visual modalities. These countermeasures showcase the utility of adopting eye-tracking technologies in the context of driver monitoring and advanced driver's assistance systems. They enhance safety as a safeguard for the increased use of devices such as in-vehicle infotainment systems. Results show that countermeasures effectively redirect drivers’ attention to the road, with higher on-road gaze time. Additionally, bimodal alerts that include the visual modality are less effective at redirecting participants’ gaze on-road and result in poorer driving performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it