Blocking roads to increase the evacuation efficiency
Bibliographic record
Abstract
SUMMARY In order to evacuate as many people as possible in case of an approaching disaster, evacuation plans have to be made in advance. These plans usually consist of optimized traffic flows. Theoretically, these flows lead to an efficient evacuation, but in practice evacuees will most probably not behave like these flows without any intervention. This difference is partly caused by evacuees using roads that are unused in the optimized traffic flows case. In this paper, a new approach is investigated that can be applied to approach these flows during an evacuation: blocking the roads (i.e., making the roads inaccessible) that have a flow equal to zero in the optimal traffic flows. This approach is expected to be effective because the people are forced to behave in the direction of the optimized traffic flows. In a case study, this approach turns out to be effective. For two different cases, the efficiency of the evacuation (a function of the arrivals) improves with respectively 10.0% and 13.4% when the zero‐flow links are blocked compared with an evacuation without any intervention. Copyright © 2012 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".