Human Factors Considerations in the Design of Rumble Strips
Bibliographic record
Abstract
Although a number of technical reports have considered different aspects of construction on crash statistics, human factors considerations are less prevalent, and no study has examined the perceptual consequence of altering the frequency of the repetition pattern. In experiment 1, the effect of frequency on perceived urgency in an auditory-only simulation of rumble strips was considered using a magnitude-estimation task. Results indicated that the ideal frequency range (yielding the highest urgency) was between 12.5 to 25 Hertz (Hz), which is lower than the range produced by typical rumble strip spacing. A psycho-acoustic explanation of this result is that the frequency range between 12.5 to 25 Hz is within the range in which sequential noise bursts can be resolved but below the range in which noise bursts fuse and give rise to pitch perception. In experiment 2, participants estimated pitch strength and matched the pitch of simulated rumble sound to a pure tone. As expected, pitch strength estimates and the accuracy of pitch matches were consistently low between 17 to 50 Hz but increased linearly with frequency beyond 50 Hz. On the basis of this auditory-only simulation, it appears that rumble strip spacing leading to audible but infra-pitch sound is ideal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".