Advanced Transit Signal Priority Control with Online Microsimulation-Based Transit Prediction Model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An advanced transit signal priority (TSP) control method is presented: it provides priority operation in response to real-time traffic and transit conditions. A high-performance online microscopic simulation model was developed for the purpose of predicting transit travel time along an intersection approach. The proposed method was evaluated through application to a hypothetical intersection with a nearside bus stop. The performance of the proposed method was compared with that of normal signal operation without TSP and a conventional signal priority method. The experimental results indicated that the developed method provided efficient and effective priority operation for both transit vehicles and automobiles. The proposed method significantly reduced transit vehicle delays as well as side-street traffic delay compared with conventional active priority control.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it