Bibliographic record
Abstract
This paper offers a more complete picture of the capacity change mechanism at a diverge bottleneck caused by a queue from an exit ramp moving upstream onto the freeway. Detailed observations collected by videos during a 4-day period from an expressway in Bangkok, Thailand, showed that traffic states during bottleneck activation at the diverge site could be categorized into three distinct states with different levels of capacity according to vehicle speeds on through movement lanes and the rates of lane change maneuvers near the off-ramp queue. The data indicated that the transitions of traffic states were caused primarily by the changes in exit flows. The lower capacity was initiated by a more restrictive off-ramp flow that caused some cut-through vehicles on the adjacent lane to impede through movement traffic. Once the exit flow increased, impeding exit vehicles could move out of the adjacent through lane and higher capacity could be restored. These findings point to automatic off-ramp control strategies that would generate higher bottleneck capacities through detecting traffic speeds on freeway through lanes. These findings advance the present knowledge in traffic flow theory that will enable traffic researchers to understand more fully the traffic phenomena at a diverge bottleneck and will help traffic engineers to operate freeway traffic properly.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".