Modified Guidelines for Left-Turn Lane Geometry at Intersections
Bibliographic record
Abstract
Left-turn vehicles need sufficient sight distance to decide when it is safe to turn left and cross the lane(s) used by the opposing traffic. The current policy of the American Association of State Highway and Transportation Officials (AASHTO) recommends that the adequacy of sight distance for left-turn vehicles should be checked because the opposing left-turn vehicles can block a driver’s view of the oncoming traffic. Previous studies have established guidelines for various intersection geometric elements (offset between opposing left-turn lanes, left-turn lane length, and left-turn lane-line width) to ensure that adequate sight distance is provided for left-turn vehicles. However, these guidelines are based on overestimation of the available sight distance. This results in underestimating the requirements for intersection elements. This paper develops modified analytical models and guidelines for various intersection elements, based on the actual available sight distance. The median opening is also introduced as a variable in the models. The results show that the existing guidelines for minimum offset and left-turn lane length are inadequate generally at low and high speeds, differing from the modified guidelines by more than 100 and 15%, respectively. The existing guidelines for minimum lane-line width are also inadequate for low percentiles (by 0.17m at an offset of −0.3m). The modified guidelines ensure that the adequate sight distance for left-turn vehicles is provided at intersections, and therefore should be of interest to traffic and geometric design engineers.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".