Safe System Intersection Application for Edmonton Capital Region - Pilot Project
Bibliographic record
Abstract
The Capital Region Intersection Safety Partnership (CRISP) conducted a pilot project on engineering applications of the Safe System approach. CRISP retained the Monash University Accident Research Centre (MUARC) in Melbourne, Australia to lead the project and apply the Safe System road safety philosophy to selected ‘poorly performing’ intersections in the City of Edmonton, Strathcona County and City of St. Albert (CRISP partner jurisdictions). The intent was to highlight differences between a traditional road-safety approach and a Safe System approach which might inform policy development. Safe System is a road safety philosophy believing that an individual’s safety is paramount to any other benefit which the transport network provides. Safe System does not tolerate serious injury and fatal collisions, regardless of the benefits that road users receive. This contrasts with current safety attitudes. For example in 2010 there were 2,227 fatalities and 11,226 serious injuries on Canadian roads that are accepted as a consequence of our transportation system. Despite this philosophical disparity there is evidence that attitudes are changing. MUARC’S literature review found a growing world-wide willingness to consider intersection geometries that emphasise reduced speeds or improved impact angles. Roundabouts in particular are increasingly seen as a reasonable and safer alternative to traffic signals. For this project MUARC applied their Kinetic Energy Management Model (KEMM) to sixteen problematic intersections in the Capital Region. KEMM is a conceptual model for evaluating the transfer of kinetic energy exchanged during a vehicular collision. Given vehicle impact speed and angle KEMM determines the amount of energy received by the human occupants and the likelihood that that energy will cause serious injury or death. KEMM quantified the probability of a fatal or serious injury outcome for the existing geometries of the problematic intersections as well as several alternatives. KEMM also tested the sensitivity of impact speed. The results showed which intersection geometries performed better with respect to risk, and which intersection geometries or treatments can be Safe System compliant. CRISP then sponsored a workshop for local transportation engineers to assess the feasibility of Safe System compliant treatments on the problematic intersections. There was strong interest in many of the treatments, including some innovative and previously untested treatments provided by the MUARC team. One surprising result from the workshop was the reluctance of local engineers to favour reduced speed limits or platform intersections, despite their relatively low implementation cost and strong safety benefits.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.059 | 0.010 |
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".