Exploring Effects of Area-Wide Traffic Calming Measures on Urban Road Sustainable Safety
Bibliographic record
Abstract
Traffic calming schemes refer to a combination of road network planning and engineering measures to minimize undesirable effects of traffic in residential areas. The traffic calming role in urban road network management is, indeed, to enhance road safety as well as other aspects of liveability for the citizens; in this context accident reduction can be a realistic objective. Several studies highlight that traffic calming treatments can significantly reduce road accidents in urban areas. Nevertheless, the increase of the accident rate per kilometre travelled has been found in urban areas as result of the so-called accident migration phenomenon. Starting from these considerations, the paper discusses the effects of traffic calming measures on road safety. The paper also aims to provide a concise overview of knowledge on the potential of the meta-analysis method in detecting the true effect of traffic calming measures on road safety. Therefore, the role of the road network planning and the characteristics of urban road network that have to be consistent to the traffic calming objectives are examined. Finally, authors suggest a methodological procedure for implementing a traffic calming zone in residential areas, from planning level to road design.
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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 | 0.049 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.020 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".