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Cited by 751

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Self-Organizing Pedestrian Movement

Helbing, Dirk, Molnár, Péter, Farkas, Illés J, Bolay, Kai·2001·Environment and Planning B: Planning and Design

Abstract

Although pedestrians have individual preferences, aims, and destinations, the dynamics of pedestrian crowds is surprisingly predictable. Pedestrians can move freely only at small pedestrian densities. Otherwise their motion is affected by repulsive interactions with other pedestrians, giving rise to self-organization phenomena. Examples of the resulting patterns of motion are separate lanes of uniform walking direction in crowds of oppositely moving pedestrians or oscillations of the passing direction at bottlenecks. If pedestrians leave footprints on deformable ground (for example, in green spaces such as public parks) this additionally causes attractive interactions which are mediated by modifications of their environment. In such cases, systems of pedestrian trails will evolve over time. The corresponding computer simulations are a valuable tool for developing optimized pedestrian facilities and way systems.

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Crossref · 10.1068/b2697

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Metadata

Authors
Helbing, D., Molnár, P., Farkas, I. J., & Bolay, K.
Venue
Environment and Planning B: Planning and Design
Published
2001-06
Volume
28
Issue
3
Pages
361-383
ISSN
  • 0265-8135 (ISSN-L)
  • 1472-3417
OpenAlex
W2033921269
Cited by
751
References
1
FWCI
31.84
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Self-Organizing Pedestrian Movement. https://app.cochat.ai/papers/10.1068/b2697
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Helbing, D., Molnár, P., Farkas, I. J., & Bolay, K. (2001). Self-Organizing Pedestrian Movement. Environment and Planning B: Planning and Design. https://doi.org/10.1068/b2697

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.