Locator Tones for Pedestrian Signals
Bibliographic record
Abstract
The two primary problems experienced by visually impaired persons at pedestrian-actuated intersections are determining whether there is a pushbutton and locating the push button. Many countries use accessible pedestrian signals much more widely than has been done in the United States, and a number of these—including Australia, Hong Kong, Sweden, Denmark, Germany, Belgium, and Austria—routinely require the use of a locator tone. Typically emanating from the push-button housing, a pushbutton locator tone indicates to pedestrians that they are expected to push a button to request a pedestrian phase. It enables visually impaired pedestrians to locate the push button quickly and efficiently. Research was undertaken to determine the effect of locator tone repetition rate on efficiency of pedestrians’ location of the push-button pole. Repetition rates of 1.0 and 1.5 Hz resulted in equal pole location speed, faster than that for the 0.5 Hz repetition rate, and were preferred over the 0.5 Hz repetition rate. Locator tones 2 dB above ambient sound resulted in faster pole location than did tones 5 dB and 10 dB above ambient sound. Push-button locator tones should have a standardized repetition rate between 1.0 Hz and 1.2 Hz so that it may be ensured that visually impaired pedestrians can efficiently locate push buttons. Locator tones need be no more than 5 dB louder than ambient traffic sound.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".