Safety and Operational Assessment of Rural Free Right-Turn Ramp Intersections
Bibliographic record
Abstract
Free right-turn (FRT) ramps are alternative right-turn lane designs for intersecting highways. As of 2023, 79 FRT ramps exist at 68 rural highway intersections in Nebraska. FRT ramps may be located on three-legged or four-legged intersections and may be on the minor, the major, or both minor and major approaches of the same intersection. This research compared the 68 rural FRT intersections to 24 similar non-FRT rural intersections to identify differences in crash frequency and crash rate and tested for statistical significance using a two-sample t-test. Crash data were obtained for the ten- year period of 2010-2019, with a focus on crashes reported within a quarter mile of each intersection leg. Forty different comparisons were made between the FRT and non-FRT intersections, testing varying intersection legs, AADT, and location of the FRT ramp on the major, minor, or both approaches. The results of this analysis indicated a lack of any statistically significant difference in crash frequency or crash rate among the rural FRT ramp and rural non-FRT intersections. In addition to the safety analysis, a conflict analysis was conducted to analyze the vehicle interactions between right-turning vehicles at the FRT ramp intersections and non-FRT intersections. Miovision Scout video recording equipment was used to record the traffic conflicts over 72 hours at six FRT intersections of varying AADT and the number of intersection legs. Six non-FRT intersections were paired with the FRT intersections and the conflict experienced by right-turn movement on the same approach as its FRT counterpart was observed. The conflict analysis showed that non-FRT right- turns experienced higher conflicts per 1000 entering right-turning vehicles than the FRT ramp intersections. It was concluded that the presence of FRT ramps at rural intersections does not affect the crash frequency or crash rate experienced. It was also concluded that conflict is reduced between right-turning vehicles and other traffic present at the intersection when an FRT ramp is present, especially compared to non-FRT intersections where no exclusive right-turn lane is present on the major approach. It is recommended that future research assess additional operational benefits of FRT ramps, such as delay and travel time. Advisor: Aemal Khattak
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".