Warrant Methodology for Evaluating and Ranking Transit Pass-Through Lanes at Freeway Interchanges
Bibliographic record
Abstract
The provision of transit vehicle priority is often motivated by opportunities to reduce person-delay within the transportation network, increase transit reliability and speed, reduce transit operating costs, and/or encourage transit use due to the environmental and social benefits often associated with transit. Within a freeway environment, one form of transit vehicle priority is the provision of transit “pass-through” lanes at interchanges. “Pass-through” lanes allow a transit vehicle to exit the freeway at an interchange, cross straight through the intersecting arterial road, and re-enter the freeway. This treatment allows transit vehicles to by-pass congestion on the mainline between the beginning of the off-ramp and the end of the on-ramp. The objective of this paper is to outline a methodology that can be applied by practitioners to evaluate if transit “pass-through” lanes are economically warranted at a given interchange, and to provide a method for prioritizing candidate locations. The warrant provides an objective and consistent decision making method, reduces the effort required for practitioners to assess the need for “pass-through” treatment at a given interchange, and helps ensure that limited resources are directed towards interchanges which are expected to experience the greatest benefit per dollar spent. The proposed methodology is based on an analytical approach that compares the value of travel time savings (for passengers and transit vehicles) with the construction and maintenance costs of the transit “pass-through” lane treatment. The methodology is demonstrated through application at a candidate freeway interchange in southern Ontario.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".