Reliability of Intergreen Interval Based on Combined Dilemma and Option Zones
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
Currently, dilemma and option zones’ failures are independently used to analyze the intergreen interval at signalized intersections. Therefore, the present research work was initiated to integrate these failures. First, the dilemma and option zones were modeled using the first-order second-moment method. Then, game theory was used to model the association between the dilemma and option failures. The failure probabilities of the dilemma and option zones were evaluated for various traffic conditions using Monte-Carlo simulation considering the Nash equilibrium. Next, the overall system probability was analyzed, based on the combined dilemma and option failures, given different intergreen intervals, speeds, and coefficients of variation. Finally, the study proposed a methodology for identifying the intergreen interval to limit system failure. This would aid practitioners in designing traffic lights at intersections and keeping proper intergreen intervals to limit the dilemma and option failures.
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.
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 | 0.000 | 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 it