Reliability estimation of public bus routes: Applicability of multivariate adaptive regression splines approach
Bibliographic record
Abstract
The performance of public bus lines is generally evaluated by comparing demand and ridership. However, reliability gain or loss by a proposed bus route should also be considered in the decision-making process to ensure a service that is preferable for users and operable for providers. In this study, it is aimed to provide a tool for predicting the reliability of a proposed bus route by considering route layout and traffic conditions. Travel time based reliability is predicted by using a novel nonparametric method, multivariate adaptive regression splines (MARS). Some critical thresholds of route layout parameters that should be considered for higher reliability are found. It is concluded that route lengths longer than 10 km, and number of intersections over 22 considerably decrease whole day based reliability. For peak hour based reliability, the types and numbers of intersections are found to be more efficient than the ones in whole day based model and a reliability regulator impact of roundabout numbers under nine is observed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".