Factors associated with compliance rate at pedestrian crosswalks with Rectangular Rapid Flashing Beacon
Bibliographic record
Abstract
In the recent decade, Rectangular Rapid Flashing Beacon (RRFB) has been introduced and widely installed across North America to improve pedestrians’ safety at crosswalks. While the treatment has been reported to be effective in improving safety, relatively few studies have been conducted to explore the factors associated with its effectiveness. This study investigates the effect of road characteristics, environmental factors, and device specification on vehicles’ yielding compliance, used as a surrogate measure of safety. Nineteen crosswalks within the City of Calgary were chosen for field study. An ordinary least squares regression model is applied to identify the factors that affect the compliance rate. It is found that type of road, daily traffic volume, posted speed limit, median, and rainy weather have significant impacts on the compliance rate. Besides, the result suggests using smaller size beacons and installing them above the pedestrian sign to improve safety to its fullest at RRFB-enhanced crosswalks.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".