Planning the most suitable travel speed for high frequency railway lines
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a new method to calculate the most suitable travel speed for high frequency railway lines to achieve as much capacity as possible for congested railway lines. The method calculates the most suitable travel speed based on the braking distance and information about the interlocking system. Based on the braking distance it is possible to calculate the minimum headway time, and thereby determine the buffer time when knowing the frequency. Hence the headway time can be divided into minimum headway time and buffer time. The buffer time is an indicator for the spare capacity of the railway line, and the more buffer time on the railway line, the better punctuality and the better possibilities to run more trains. Based on the described method a case example from the suburban railway lines of Copenhagen will be shown. The case example shows that a reduction of the maximum travel speed by 6% in central Copenhagen can increase the capacity by 11%. The increased capacity will improve the punctuality of the trains in central Copenhagen – even though some of the capacity will be used to run more trains through Copenhagen.
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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