Toward a Simulation-based Approach for Emergency Evacuation Route Planning in Metro Stations
Bibliographic record
Abstract
This paper presents a systematic simulation-based approach with detailed step-by-step procedures for route planning in emergency evacuation in metro stations. In accordance with emergency evacuation mechanism analysis, the length of evacuation route (L), the time of evacuation (T) and the density of pedestrian flow (D) are identified as critical factors that affect the performance of emergency evacuation. With all the critical factors, such as L, T and D, taken into account, a comprehensive multi-attribute decision algorithm is developed in order to optimize the selection of evacuation route under emergency. Taking the Hongshan Station in Wuhan metro systems as an example, the Anylogic tool is used to simulate the scenario of evacuation route planning in case of a fire. The simulation results regarding the evacuation performance indicators are analyzed and compared between the traditional and proposed approaches. Results indicate that the proposed approach can reduce the evacuation time without increasing the route length, and improve greatly the crowded conditions of pedestrian flow. The developed approach can provide guidelines and support for the optimization of evacuation route planning under emergency conditions.
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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 | 0.001 |
| 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".