The Effect of Driver Eye Height on Speed Choice, Lane-Keeping, and Car-Following Behavior: Results of Two Driving Simulator Studies
Bibliographic record
Abstract
OBJECTIVE: Two simulator studies were conducted that assessed the effect of driver eye height on speed choice, lane-keeping, and car-following behavior. The effect of eye height on the subjective variables of mental workload, frustration, and confidence was also investigated, as was the contribution of drivers' aggression. METHODS: A total of 43 participants drove a simulated route while seated at two different eye heights: one that represented the view of the road from a large SUV and one that represented the view of the road from a small sports car. Driving scenarios were comprised of both open road and car-following segments. Dependent variables included driver-selected speed, speed variability, lane position, following distance to a slower-moving lead vehicle, and the subjective variables of frustration, confidence, and mental workload. RESULTS: When viewing the road from a high eye height, drivers drove faster, with more variability, and were less able to maintain a consistent position within the lane than when viewing the road from a low eye height. Driver eye height did not influence following distance to a slower-moving lead vehicle. Driver aggression had no effect on any of the dependent variables except level of frustration. CONCLUSIONS: The two studies demonstrate that, when they are not able to reference a speedometer, drivers choose to drive faster when they view the road from an eye height that is representative of a large SUV compared to that of a small sports car. There is a need to educate drivers of SUVs and other tall vehicles of this perceptual phenomenon in order to prevent collisions that may occur in conditions where it is impossible for drivers to base their speed selection solely on posted speed limits, such as in inclement weather.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".