Proposal for traffic light operation to reduce vehicle conflicts at the intersection between Av. Peru and Av. Canada in the district of San Martin de Porres
Bibliographic record
Abstract
La presente investigación tiene como problemática el tráfico vehicular entre la Avenida Perú y Avenida Canadá, ubicada en el distrito de San Martin de Porres - Lima - Perú. El proyecto se basa, principalmente, en optimizar los tiempos del semáforo, el cual será validado a través de una modelación en el programa Vissim. El modelo consta de cinco fases. Para la primera, se realizaron visitas en campo a la intersección y se recopiló información como el ciclo del semáforo, aforos vehiculares y peatonales, longitud de cola y registro fotográfico del estado actual. Seguidamente, de la información obtenida, se modeló la situación actual utilizando el software Vissim. En la tercera fase, se proyectaron tres propuestas: incrementación de dos tiempos semafóricos, incrementar el tiempo semafórico y disminuir el tiempo semafórico. Con ello, se realiza una comparación de los resultados entre la situación actual y las situaciones propuestas. Finalmente, con el escenario Nª01 se obtuvo en la microsimulación con el software Vissim, una reducción en la longitud de cola de la avenida Perú en 30% y en la avenida Canadá en 18%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".