Safety Evaluation of Red-Light Cameras and Dynamic Speed Display Signs Within the City of Ottawa
Bibliographic record
Abstract
This thesis evaluates the safety impacts of red-light cameras (RLCs) and Dynamic Speed Display Signs (DSDSs) in Ottawa, Canada. The study examines the safety impacts of RLCs on safety performance, using collision records, and driver behaviour using surrogate safety measures. The safety impacts of DSDSs on driver behaviour are evaluated using speed analysis. An empirical Bayes method for RLCs showed a significant impact, where total and PDO collisions increased while injury and fatal collisions decreased. The impact of RLCs also depended on the collision types, where sideswipe, rear-end, and SMV collisions increased, but the angle and turning collisions decreased. The increase in rear-end collisions was also examined through an analysis of traffic conflicts. The results indicated that treated sites had significantly more severe rear-end conflicts that had likely resulted from harder deceleration rates. Speed analysis for DSDSs indicated drivers reduced their speed when they saw their actual speed on DSDSs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".