Signal Timing Optimization for Transit Priority at Near-Saturated Intersections
Bibliographic record
Abstract
Transit signal priority is a useful way to improve transit operations in urban networks. Most of the existing studies have been conducted in conditions with low saturation to avoid the detrimental effects of vehicles without priority. However, from the public transit point of view, it is more meaningful to assign transit signal priority when the degree of the saturation intersections is high. This study proposes a signal control model for transit signal priority to minimize the overall delay at near-saturated intersection. The delay increment is calculated in three scenarios for buses and private vehicles according to the dissipation time of the vehicular queue. A set of constrains are set up to avoid queue overflows and to ensure the rationalization of the signal timing. The proposed control model is tested based on a case study and numerical experiments. The results show that the proposed model can reduce the total person delay at near-saturated intersections. The length of priority time, degree of saturation, and number of lanes are the three main influencing factors. More than 6% reductions in person delay can be obtained for undersaturated intersections when the priority time is less than 5 s. Moreover, even when the intersection saturation is 0.95, the bus signal priority can be applied if only the priority time is less than 5 s.
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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 | 0.000 |
| 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".