Performance of Advance Warning for End of Green System for High-Speed Signalized Intersections
Bibliographic record
Abstract
A major difficulty with traffic signal operation on high-speed approaches is the dilemma faced by approaching motorists when the downstream signal turns yellow. Should the motorists stop or proceed through the intersection? Crashes that may occur at these intersections result in excessive property damage and personal injury because of the high speeds involved. The Texas Transportation Institute has developed a new system named the Advance Warning for End of Green System (AWEGS) for application at high-speed signalized intersections. Typically, dilemma zone detection strategy is based on a certain approach speed (typically the 85th percentile). AWEGS provides protection for the majority of motorists who are not covered by the dilemma zone treatment. AWEGS provides advance warning to motorists by using signs mounted on the roadside. These signs (Be Prepared To Stop When Flashing) would flash a beacon about 5 to 6 s before the onset of the yellow signal for high-speed approaches. Similar systems have been implemented in Canada and in a few U.S. states that use the trailing-green approach, which results in loss of dilemma zone protection every cycle. AWEGS, however, is almost completely independent of the traffic signal controller, and hence the signal controller would continue to provide the dilemma zone protection for which it was designed. The system was implemented at two sites in Waco and Brenham, Texas. Results of AWEGS implementation illustrated an improvement in traffic operations. AWEGS consistently enhanced the dilemma zone protection at intersections and reduced red light running by about 40%.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".