Bibliographic record
Abstract
Intersection sight distance is an important design element. A stopped vehicle on the minor road needs sufficient sight distance to depart (cross, turn left, or turn right) safely, even though an approaching vehicle on the major road comes into view. Current AASHTO policy assumes that both minor and major roads are straight and intersect at right angles. Previous research has addressed sight distance for stop-control intersections on three-dimensional alignments for obstructions inside the horizontal curve and for intersection and major-road vehicle (object) on the curve. The results of the research presented in this paper extend previous research work by (a) allowing the object to be anywhere on the horizontal curve or tangent, (b) allowing the horizontal and vertical curves to overlap partially, and (c) considering the case in which the obstruction lies outside the horizontal curve. The obstruction location was formulated through use of a simple variable that takes the value of +1 or −1 for an obstruction, respectively, inside or outside the horizontal curve. Design aids for the required minimum lateral clearances (from the minor and major roads) are presented for different radii of horizontal curve and major-road design speeds. Application of the model is illustrated through a numerical example. The presented model and guidelines, which are general and easy to use, should be of interest to highway designers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".