Bus Trajectory Optimization With Holding, Speed and Traffic Signal Actuation in Controlled Transit Systems
Bibliographic record
Abstract
We propose an optimal actuation of operational commands for regularizing bus headways. Assuming that a transit headway control system manages the bus operation by issuing reference arrival times at the next station for a bus, the problem is how to implement the control decisions for the bus in terms of three nonexclusive alternative actions: holding the bus at stops; varying bus speeds; and controlling traffic lights. Mathematical programming provides the basis of the approach. The constraints specify the bus trajectory model and the operator objectives are formulated as a multi-objective cost function solved by a lexicographic method. Results for a bus run on a single segment between two stops highlight the properties of the solution. A simulation study of an entire transit corridor in Quebec City, Canada, shows the advantage of the method over both headway control based on pure holding at stops and on one that combines holding and absolute transit signal priority.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".