Personal space, evasive movement and pedestrian level of service
Bibliographic record
Abstract
SUMMARY This study proposed a behavioral theory‐based approach to better assess pedestrian levels of service for sidewalks, using the concepts of personal space and pedestrian evasive movements. Data from pedestrian interviews and video recordings at 28 commercial, residential, and leisure locations were used to analyze the effects of pedestrian movements on pedestrian perceived levels of service. With these results, a new measure of pedestrian level of service was developed. With the use of a separate validation sample, the revised levels of service obtained were found to be more consistent with the pedestrian perceived levels than the levels prescribed by the Korean Highway Capacity Manual. Hence, this research recommended the use of the revised measures for pedestrian level of service in the design and evaluation of pedestrian facilities. We also found that pedestrian evasive movements on sidewalks could better explain pedestrians' perception of the levels of service for a given facility. Moreover, pedestrian evasive movements were found to be sensitive to the width of the sidewalk and pedestrian volume. Copyright © 2013 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".