Effects of Safety Facilities on Driver Distance Perception in Expressway Tunnels
Bibliographic record
Abstract
We investigated the effects of four safety facilities in expressway tunnels—information boards, flashing lights, human-voice broadcasts, and siren broadcasts—on driver distance perception by questionnaire surveys and field experiments. Results from a survey questionnaire given to 436 drivers indicated that each of the facilities, except the human-voice broadcast, was perceived to increase the driving safety. Consistently, results from field experiments involving 150 participants in China’s Xingshuliang Tunnel indicated that information boards, flashing lights, and siren broadcasts increased the distance perception accuracy of drivers, while human-voice broadcasts decreased this accuracy. The results of human-voice broadcasts may be due to the fact that drivers could not catch and understand the information they heard from human-voice broadcasts while driving in tunnels. This research can assist engineers in identifying the effective safety facilities in tunnels and provide a basis for prioritizing the implementation of these facilities, ultimately increasing driver distance perception accuracy and decreasing rear-end collisions.
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".