Relationship between Speed, Lateral Placement, and Drivers’ Eye Movement at Two-Lane Rural Highways
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
A number of previous studies have investigated driver behaviors including speed and lateral placement in curved sections of highways. However, few studies attempted to empirically address relationships considering other factors, such as driver’s eye-fixation distributions and illuminations, which are also believed to be relevant to highway safety. This study consists of field experiments to examine driver behaviors under different geometric and illumination conditions in two-lane rural highways. In the experiment, drivers’ eye movements, which have been considered as surrogate of drivers’ visual attention, are investigated by using a head-mounted eye-movement tracking system. Regression models are developed to show the relationship among the data, and the results show that there are significant differences in driver’s eye movements under different geometric and illumination conditions. These findings give traffic engineers practical suggestions when implementing traffic control devices to increase safety on curved sections of two-lane rural highways.
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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