Stop-Controlled Intersection Sight Distance: Minor Road on Tangent of Horizontal Curve
Bibliographic record
Abstract
Sight distance at the intersection of a minor road (controlled by a stop sign) and a major road is an important element of road safety. Several models have been recently developed for the analysis of sight distance at intersections involving horizontal curves on the major road. All these models assume that the intersection lies within the horizontal curve. There are situations, however, when the intersection lies within one of the tangents of the horizontal curve. This case would adversely affect sight distance, especially when the horizontal curve is sharp and the minor road is close to the horizontal curve. This paper develops a new mathematical model for sight distance analysis that explicitly addresses the case where the intersection lies within the tangents of the horizontal curve. The obstruction may be located within the tangent or within the horizontal curve, or located inside or outside of the horizontal curve. Using the model, graphical aids for the required obstruction distances from the major and minor roads, to satisfy sight distance requirements, are developed. The developed model can be used to evaluate sight distance for existing or new intersections.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".