Driver tolerance of lateral accelerations on horizontal curves
Bibliographic record
Abstract
There are many roadways where existing horizontal curves fail to meet minimum geometric design standards for financial or geographic reasons. Advisory speeds, typically set with a ball-bank indicator, are posted on these curves to ensure that drivers are not subjected to uncomfortable levels of lateral accelerations as they negotiate the curve. The threshold levels of lateral acceleration as estimated by ball-bank indicators vary considerably between jurisdictions with many still basing their guidelines on studies dating back to the 1930s and 1940s. This study investigated present day ball-bank indicator tolerance levels by analyzing actual driver behaviour on 30 curves posted with advisory speeds in New Brunswick. A unique method of data collection involving digital video analysis enabled the development of vehicle speed profiles approaching and throughout the curves. The results indicated that drivers tolerate higher levels of discomfort as they navigate curves than currently assumed. This finding justifies raising the ball-bank indicator threshold levels used for posting advisory speeds. Inconsistencies between actual posted advisory speeds, policy guidelines, and jurisdictional implementation have also been identified. Recommendations address both short and long-term goals of updating ball-bank indicator thresholds used for signing to levels that better represent driver behaviour. Longer-term recommendations address the development of uniform signing standards across Canada so that driver expectation will not be violated between jurisdictions.
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 | 0.001 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".