Development and evaluation of a microscopic overtaking gap acceptance model for two-lane highways
Bibliographic record
Abstract
A microscopic gap acceptance model is presented that simulates overtaking behavior on two-lane highways. The decision to initiate overtaking is expressed as a function of each driver’s perception of the expected time-to-collision (TTC) with the nearest opposing vehicle at the end of maneuver. The available gap is accepted if the driver’s perception of TTC exceeds a predetermined threshold for safe return (critical TTC). The gap acceptance model is calibrated and validated based on overtaking video-recording data for a two-lane highway. The overtaking gap acceptance model is then compared, for consistency and transferability, with independent aggregate field data, as well as with two other simulation models and values given in the Highway Capacity Manual for similar two-lane highways. The gap acceptance simulation demonstrated that the proposed overtaking model is able to provide reliable measures of traffic attributes for two-lane highway operation, as verified experimentally.
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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 | 0.000 |
| 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".