Understanding Pedestrian Interactive Behaviors under the Different Level of Services on Stairways
Bibliographic record
Abstract
Stairways serve as important walking facilities for pedestrians, especially in metro stations, but researches of pedestrian traffic on stairways are not sufficient. This paper investigates pedestrian interactive behaviors (PIBs) under the different level of services (LOS) on stairways, including overtaking behavior and evasive behavior on stairways. Macro and micro indicators are proposed and calculated based on field observation collected from two stairway flights in a certain metro station in Shanghai, China. Results of macro indicators reveal that the characteristics of overtaking behavior and evasive behavior have both similarities and differences. As for similarities, neither of these two types of behaviors would occur under extremely low or high densities, representing LOS A or LOS F. Under other ranges of density, occurrence intensities of pedestrian interactive behaviors on stairways are different. Overtaking behavior intensity shows a rapid increase trend with the density from low to medium, while evasive behavior intensity keeps a certain value. Results of micro indictors show that the available space for overtaking behavior and evasive behavior is the main factor contributing to the above similarities and differences. Characteristics of PIBs under the different LOS present in highway capacity manual are discussed based on field observations. Findings of this research are helpful to understand the knowledge of PIBs on stairways for a better stairway traffic design and level of service evaluation.
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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".