Impacts of road and rail temporal traffic variations on grade crossings exposure, design, and regulation in Manitoba
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Transport Canada has recently published regulations and guidance for design considerations at grade crossings. Cross-product, or the product of average daily vehicles and trains, is one of several criteria that define warning system requirements. While based on readily available data, application of the cross-product may oversimplify the interactions between vehicles and trains at a crossing by failing to account for known temporal variations in both modes. Through two analyses, this paper investigates the effects of temporal traffic variations on estimated grade crossing exposure and develops insights about alternatives to quantify this exposure. The first analysis considers the effect of daily road traffic variations on grade crossing exposure and compliance at 240 rural grade crossings. Nine of the studied crossings (4%) experienced at least one day for which the estimated single-day exposure indicated a need for an upgraded warning system, based on the cross-product criterion alone. Conversely, 91 crossings (38%) had warning systems that would be considered over-designed for the entire year. The second analysis considers the effect of hourly road and rail traffic variations on grade crossing exposure at 13 urban grade crossings by estimating hourly cross-product equivalents. Each of the eleven studied gated crossings featured at least seven hourly cross-product equivalents that exceeded the cross-product threshold for gated crossings. The findings demonstrate that the cross-product may misrepresent vehicle-train interactions at a crossing by suppressing temporal variability in road and rail traffic. Consequently, these variations should be considered in design and prioritization decisions for reducing risk and delay at grade crossings.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it