Expert evaluation of traffic signs: conventional vs. alternative designs
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
Traffic sign comprehension is significantly affected by their compliance with ergonomics design principles. Despite the UN Convention, designs vary among countries. The goal of this study was to establish theoretical and methodological bases for evaluating the design of conventional and alternative signs. Thirty-one conventional signs and 1–3 alternatives for each conventional sign were evaluated for their compliance with three ergonomics guidelines for sign design: physical and conceptual compatibility, familiarity and standardisation. Twenty-seven human factors and ergonomics experts from 10 countries evaluated the signs relative to their compliance with the guidelines. Analysis of variance across alternatives revealed that for 19 of the 31 signs, an alternative design received a significantly higher rating in its ergonomics design than the conventional sign with the same meaning. We also found a very high correlation between the experts’ ratings and comprehension from previous studies. In conclusion, many countries use signs for which better alternative designs exist, and therefore UN Convention signs should be re-examined, and ergonomics experts evaluation can serve as a good surrogate for road users’ comprehension surveys.Practitioner summary: This study presents theoretical and methodological bases for evaluating the design of UN Conventional and alternative traffic signs. Human factors and ergonomics experts evaluated 31 conventional and 68 alternative road signs, based on ergonomics principles for sign design. Results indicated the need to re-examine poorly designed UN Convention signs.
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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 | 0.001 | 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) | 0.009 | 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 it