A Dynamic Time Warping Algorithm Based Analysis of Pedestrian Shockwaves at Bottleneck
Bibliographic record
Abstract
Since the quantitative methodology analysis of the high-density pedestrian shockwaves at a bottleneck is limited, this paper proposes a dynamic time warping (DTW) algorithm for identifying, analyzing, and verifying the shockwaves. A set of real-world trajectory data is used to illustrate the proposed algorithm. Results show that the DTW algorithm is capable of depicting the pedestrian shockwaves elaborately and accurately. Results also show that the shockwave velocity is unsteady, as throughout time the gathering wave velocity and the evanescent wave velocity are decreasing and increasing, respectively. The mutual influence between followers and leaders is decreased when the shockwave spreads. There is a linear relationship between the shockwave velocity and density. Furthermore, singularities present a potential match solution to help identify the changing of pedestrian behaviors. The DTW algorithm for evaluating the pedestrian system stability has significant intrinsic features in the pedestrian traffic control and management.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".