P-TRANE: Modeling Bus Transit Network Evolution in a GIS-Based Framework
Bibliographic record
Abstract
This paper describes the development and the main components of a simulation framework, named P-TRANE (Prediction Model of Transit Network Evolution), for modeling the bus transit network evolution. Using a GIS-based interface, P-TRANE develops predictions of changes in the bus transit network & service functionality at future time steps. These changes, triggered by the periodic service review process, are influenced by several variables such as changes in future transit ridership and future land-use. P-TRANE was developed as a transit supply prediction component for the Integrated Land Use, Transportation, & Environment (ILUTE) simulation framework, aiming to produce future bus network information for ILUTE. However, it could usefully function as a decision support system tool for transit planners and transit agencies. Preliminary model results, using the Toronto Transit Commission bus network as a case study, show that it is successful in identifying transit routes prone to frequency changes (poor performance and/or overcrowding). Furthermore, results show that the P-TRANE GIS module is a promising tool capable of proposing new bus lines, including feeder lines serving rapid transit projects/stations.
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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 | 0.019 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".