Leading Pedestrian Interval: Assessment and Implementation Guidelines
Bibliographic record
Abstract
The purpose of a leading pedestrian interval (LPI) is to provide pedestrians with the opportunity to begin crossing the street before adjacent through-movement vehicles are permitted to proceed. This procedure allows pedestrians to establish a presence in the crosswalk; this presence increases the visibility of pedestrians to drivers and therefore reduces conflicts with turning vehicles. The City of Toronto, Ontario, Canada, implemented and formally evaluated an LPI in 2005. LPIs have been added to a few more intersections since then; however, the process has not been streamlined. For LPIs to be implemented at additional locations, an implementation guide and operating standard was needed. In answer to this need, transportation services of the City of Toronto developed an implementation and assessment guideline. The purpose of the guideline is to help traffic engineers identify suitable locations for LPIs by means of a checklist, determine the appropriate length of time for the LPI with a formula, and consider operation features that would maximize the positive safety effects and minimize any negative impact on vehicular capacity. The guideline also suggests a method for measuring improvements in intersection safety as a result of LPIs. Besides introducing various components of the newly developed guide, this paper provides a review of past studies on the effectiveness of LPIs in improving pedestrian safety and a review of the state of practice in other jurisdictions in regard to implementation and operation of LPIs.
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How this classification was reachedexpand
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 | 0.005 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".