Capacity Estimation for Roundabouts with High Truck Volume Using Gap Acceptance Theory
Bibliographic record
Abstract
This study examines the effect of heavy vehicles (trucks) on entry capacity of roundabouts. The movements of vehicles were observed at 11 roundabouts in Vermont, Ontario and Wisconsin. Gap-acceptance parameters were estimated for cars and trucks separately; consistent with previous studies, it was found that critical headway and follow-up time were longer for trucks than cars. Follow-up times for truck-involved vehicle-following cases were found to be associated with central island diameter and entry angle. Gap-acceptance parameters for all entering vehicles were adjusted to a volume-weighted average of the gap-acceptance parameters for cars and trucks. Entry capacity was estimated using existing capacity models with the adjusted gap-acceptance parameters, and compared with the observed capacity at three roundabouts. The capacity models with adjusted gap-acceptance parameters estimated capacity more accurately than the models with unadjusted parameters. Microscopic traffic simulation model was also effective in representing truck characteristics and their impact on roundabout operation.
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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 | 0.000 | 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 | 0.001 |
| 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 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".