Bibliographic record
Abstract
Determining the proper location of bus stops is an important planning decision in the transit planning field. While previous efforts in the literature have suggested several advantages and disadvantages of certain bus stop placements, there has been little effort toward understanding the impacts of bus stop location on the transit system performance at the stop level of analysis. This paper evaluates the impact of bus stop location on bus stop time and stop time variation. The paper uses stop level data collected from the Société de Transport de Montréal's automatic vehicle location and automatic passenger counting systems in Montreal, Quebec, Canada. The study findings show that stop times occurring on the nearside of intersections are on average 4.2 to 5.0 s slower than stop times occurring on the farside of intersections, with no impact on stop time variation. A validation model was used to confirm the impacts of bus stop placements on stop time with data from TriMet's automated bus dispatch system in Portland, Oregon. This study offers transit planners and policy makers a better understanding of the effects of bus stop location on stop time and its variation to improve service quality while minimizing service variation at the stop level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".