Road Safety Audits: Lessons Learned for Pre-Opening Stage
Bibliographic record
Abstract
This paper summarizes the lessons learned from conducting road safety audits (RSA) at the pre-opening stage. The paper is based on the experience of the authors who have conducted a wide range of RSAs throughout Canada over the past two decades including audits of large private-public partnership (P3) projects. Typically P3 projects require a pre-opening audit prior to traffic availability when the operating consortium assumes liability for the agreement period. One of the most important lessons learned is that the pre-opening audit should be preceded by a 'preliminary' pre-opening RSA. This allows the contractor(s) ample lead time to attend to safety deficiencies that may take several weeks to remediate. Since most P3 projects are under tight time constraints and often subject to financial penalties for late delivery, it is particularly important for the contractor to be forewarned of safety-related deficiencies. Furthermore, auditors are often in the position of having to sign-off on the project before it can be made available for traffic so it is especially important that all issues are addressed prior to opening. Among the lessons learned a wide range of safety issues and deviances include: missing and improper signage, grading (sideslopes, shoulder drop-offs); improper barrier installation; location of luminaires; opportunities to improve positive guidance; excessive driver workload; unprotected hazards in the clear zone (drainage features, sign structures, etc); and safety issues concerning vulnerable road users (pedestrians and cyclists) on multi-use pathways, sidewalks or bike lanes that are part of the roadway project. For the covering abstract of this conference see ITRD record number 201211RT334E.
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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 | 0.127 | 0.232 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.018 | 0.023 |
| Open science | 0.010 | 0.012 |
| Research integrity | 0.008 | 0.021 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".