Impacts of Various Parameters on Transit Signal Priority Effectiveness
Bibliographic record
Abstract
This research examines the impacts of a number of traffic parameters on the effectiveness of a Transit Signal Priority (TSP) application. TSP is tested with the 98 B-line rapid buses along Granville Street in the City of Vancouver as a case study. VISSIM, a micro-simulation software (PTV 2002), is used to simulate TSP operation on the corridor. The traffic parameters studied include: bus approach volume, cross street volume/ capacity (v/c) ratio, bus headway, bus stop location, bus check-in detector location, left turn condition, and signal coordination. Based on results from these experiments, recommendations are provided for TSP application on Granville Street. In general, it is found that a TSP application would be most effective under a traffic condition that has moderate-to-heavy bus approach volume, little or no turning volume hindering bus movement, slight-to-moderate cross street v/c ratio, farside bus stop, and signal coordination for traffic running in the peak direction.
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".