Breakdown-Related Capacity for Freeway with Ramp Metering
Bibliographic record
Abstract
Research was conducted to better understand the breakdown phenomenon and look for ways of strategically increasing capacity and travel speed by reducing breakdowns on a section of freeway in Mississauga, Ontario, that is subject to ramp metering. The major task was to quantify the probability of breakdown as an increasing function of volume at the critical location. Data from 71 peak periods during which breakdown occurred at the critical merge were used to estimate the function, which was then used in a computer simulation of fixed- and variable-rate metering to demonstrate the potential benefits of using the probability-of-breakdown concept as a basis for ramp metering. The results indicate, for example, that variable-rate metering that complements a constant merge flow limit of 2,320 veh/h per lane could increase peak-hour throughput from about 6,460 to 6,600 veh/h at this location. They also indicate that 2,500 veh/h might be allowed, provided stringent metering for quick recovery to free flow is feasible.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".