Comparison of Safety Performance Models for Urban Roundabouts in Italy and Other Countries
Bibliographic record
Abstract
In Italy, almost half of all road crashes occur at intersections, primarily in urban areas. In recent years the widespread conversion of at-grade intersections to roundabouts has brought many safety advantages. To assess the safety benefits of roundabouts, transportation professionals need the powerful statistical tool known as the safety performance function (SPF). To date there has been no reported application of this tool to assess the relative safety performance of Italian urban roundabouts. This paper fills that void by using data sets from two municipalities in northern Italy. SPFs were estimated for each city with the negative binomial error distribution and then recalibrated for application in the other city by using the procedure described in the Highway Safety Manual. Model reliability and between-city transferability were evaluated with the cumulative residuals method. To assess how the Italian roundabout SPFs might be used to learn lessons from differences in crash experience for similar intersections elsewhere, a comparison with models from other countries is also provided. This comparison reveals that Italian roundabouts tend to be less safe. Potential reasons for this finding are explored.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".