Exploring the Effect of Boarding and Alighting Ratio on Passengers’ Behaviour at Metro Stations by Laboratory Experiments
Bibliographic record
Abstract
The objective of this work was to study the effect of the ratio between passengers boarding and alighting on the passengers’ behaviour at metro stations. A mock-up of a vehicle and the relevant portion of the platform was built to run a series of simulation experiments at University College London’s Pedestrian Accessibility and Movement Environment Laboratory (PAMELA). Different scenarios were tested based on the next generation London Underground trains. The scenarios were classified according to different load conditions. Four types of behaviour are described. In most cases boarding is first, and passengers compete for space to enter the train. In the case of alighting, first passengers are faster than the rest of alighters due to the space available on the platform as boarding passengers give way to those who are getting off the train. In addition, alighters form lanes of flow depending on the number of passengers waiting to board the train on the platform. With respect to the train, if the density inside the train is higher than 4 passengers per square metre, then the flow at the doors starts to decrease. More experiments are needed to study the relationship between platform density and boarding and alighting time.
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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".