Order–disorder transition in multidirectional crowds
Bibliographic record
Abstract
One of the archetypal examples of active flows is a busy concourse crossed by people moving in different directions according to their personal destinations. When the crowd is isotropic-comprising individuals moving in all different directions-the collective motion is disordered. In contrast, if it is possible to identify two dominant directions of motion, for example in a corridor, the crowd spontaneously organizes into contraflowing lanes or stripes. In this article, we characterize the physics of the transition between these two distinct phases by using a synergy of theoretical analysis, numerical simulations, and stylized experiments. We develop a hydrodynamic theory for collisional flows of heterogeneous populations, and we analyze the stability of the disordered configuration. We identify an order-disorder transition occurring as population heterogeneity exceeds a theoretical threshold determined by the collision avoidance maneuvers of the crowd. Our prediction for the onset of pedestrian ordering is consistent with results of agent-based simulations and controlled experiments with human crowds.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".