The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Simulation of pedestrian dynamics using a two-dimensional cellular automaton
Open accessAbstract
We propose a two-dimensional cellular automaton model to simulate pedestrian traffic. It is a vmax=1 model with exclusion statistics and parallel dynamics. Long-range interactions between the pedestrians are mediated by a so-called floor field which modifies the transition rates to neighbouring cells. This field, which can be discrete or continuous, is subject to diffusion and decay. Furthermore it can be modified by the motion of the pedestrians. Therefore, the model uses an idea similar to chemotaxis, but with pedestrians following a virtual rather than a chemical trace. Our main goal is to show that the introduction of such a floor field is sufficient to model collective effects and self-organization encountered in pedestrian dynamics, e.g. lane formation in counterflow through a large corridor. As an application we also present simulations of the evacuation of a large room with reduced visibility, e.g. due to failure of lights or smoke.
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Citations
Cites
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Helbing, D., & Molnár, P. (1995) · Physical Review E · doi:10.1103/physreve.51.4282 · Cited by 6,845
Simulating dynamical features of escape panic
Helbing, D., Farkas, I., & Vicsek, T. (2000) · Nature · doi:10.1038/35035023 · Cited by 4,916
A cellular automaton model for freeway traffic
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Chowdhury, D. (2000) · Physics Reports · doi:10.1016/s0370-1573(99)00117-9 · Cited by 2,298
Statistical Physics of Vehicular Traffic and Some Related Systems
Chowdhury, D., Santen, L., & Schadschneider, A. (2000) · Cited by 1,823
Self-citationAn exactly soluble non-equilibrium system: The asymmetric simple exclusion process
Derrida, B. (1998) · Physics Reports · doi:10.1016/s0370-1573(98)00006-4 · Cited by 843
Self-organization and a dynamical transition in traffic-flow models
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The Statistics of Crowd Fluids
HENDERSON, L. F. (1971) · Nature · doi:10.1038/229381a0 · Cited by 657
Jamming transition in pedestrian counter flow
Muramatsu, M., Irie, T., & Nagatani, T. (1999) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/s0378-4371(99)00018-7 · Cited by 535
Discrete stochastic models for traffic flow
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Cited by
Statistical physics of social dynamics
Castellano, C., Fortunato, S., & Loreto, V. (2009) · Reviews of Modern Physics · doi:10.1103/revmodphys.81.591 · Cited by 4,119
Pedestrian, Crowd and Evacuation Dynamics
Helbing, D., & Johansson, A. (2009) · Encyclopedia of Complexity and Systems Science · doi:10.1007/978-0-387-30440-3_382 · Cited by 386
Physics of transport and traffic phenomena in biology: from molecular motors and cells to organisms
Chowdhury, D., Schadschneider, A., & Nishinari, K. (2005) · Physics of Life Reviews · doi:10.1016/j.plrev.2005.09.001 · Cited by 313
Self-citationAgent-based simulation of affordance-based human behaviors in emergency evacuation
Joo, J., Kim, N., Wysk, R. A., Rothrock, L., Son, Y.-J., Oh, Y.-G., & Lee, S. (2013) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2012.12.007 · Cited by 157
Human Behavioral Simulation Using Affordance-Based Agent Model
Kim, N., Joo, J., Rothrock, L., Wysk, R., & Son, Y.-J. (2011) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-21602-2_40 · Cited by 22
Metadata
- Authors
- Burstedde, C., Klauck, K., Schadschneider, A., & Zittartz, J.
- Venue
- Physica A: Statistical Mechanics and its Applications
- Publisher
- Elsevier BV
- Published
- 2001-06
- Volume
- 295
- Issue
- 3-4
- Pages
- 507-525
- ISSN
- 0378-4371 (ISSN-L)
- OpenAlex
- W2065042410
- Cited by
- 1,769
- References
- 20
- FWCI
- 52.70
- Type
- journal article
- Language
- en
- Open access
- green
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- Burstedde, C., Klauck, K., Schadschneider, A., & Zittartz, J. (2001). Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A: Statistical Mechanics and its Applications. https://doi.org/10.1016/s0378-4371(01)00141-8
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
