Bicycle-Specific Traffic Signals
Bibliographic record
Abstract
This paper presents the results of a survey of North American jurisdictions with known installations of bicycle-specific traffic signals and a review of available engineering guidance. Surveys were sent to agencies in 21 jurisdictions (19 in the United States and two in Canada). The surveys requested details on the engineering aspects of the jurisdictions' signal designs (e.g., placement, mounting height, lens diameter, backplate color, type of actuation, interval times, use of louvers, performance). Survey responses were received for 63 intersections and 149 separate signal heads, and the results highlighted current treatments and variations in similar designs. The guidance documents that were reviewed included those produced by the National Association of City Transportation Officials, New York; AASHTO, Washington, D.C.; the Transportation Association of Canada, Ottawa, Ontario; CROW, Ede, Netherlands; and the respective manuals on uniform traffic control devices of Canada, the United States, and the State of California. A subsequent review of the documents revealed consistent guidance in general with regard to the design of bicycle-specific traffic signals. Guidance on bicycle signals has grown substantially in recent years, so future designs are likely to vary less.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".