Validation of Perspective-View Concept for Estimating Road Horizontal Curvature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In three-dimensional (3D) alignments, some road geometric parameters, such as vertical curve type (crest or sag), can cause drivers to have visual illusions in perceiving the horizontal curvature that may result in erroneous decisions. Road curvature estimation is usually made based on the perspective-view (PV) information. It is hypothesized that drivers can estimate road curvature visually based on the openness magnitude of the inside edge lines which appear to the drivers as parabolas or hyperbolas. This paper further develops the PV concept and validates it using the published results of driver perceptions of 3D alignments. The analysis shows that there are statistically good relationships between the ratio of the 3D perspective radii of the crest (or sag) and flat horizontal curves, and driver perceptions. Preliminary criteria for the design of 3D alignments based on driver perceptions are presented. The PV method provides a means of incorporating driver perception into geometric design, and therefore should be of interest to highway designers and researchers.
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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 it