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The moving behavior of a large object in the crowds in a narrow channel

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  • Jiang, Rui
  • Wu, Qing-Song

Abstract

In this paper, the interaction between the large object and the pedestrians in the narrow channel is studied. The pedestrians are modelled by the lattice gas model and they are regarded as biased random walkers. The dependence of the average speed of the large object on the density of the pedestrians, the size of the large object, and the position of the large object is investigated. The simulations show that with the increase of the pedestrian density, the average speed of the large object either decreases or remains constant. It is found that when the large object is moving opposite to the pedestrians, generally it will move fast in the middle of the channel. However, if it moves in the same direction as the pedestrians, then it will move fast when it is along the wall.

Suggested Citation

  • Jiang, Rui & Wu, Qing-Song, 2006. "The moving behavior of a large object in the crowds in a narrow channel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 457-463.
  • Handle: RePEc:eee:phsmap:v:364:y:2006:i:c:p:457-463
    DOI: 10.1016/j.physa.2005.08.060
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    References listed on IDEAS

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    1. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    2. Kai Nagel & Peter Wagner & Richard Woesler, 2003. "Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling," Operations Research, INFORMS, vol. 51(5), pages 681-710, October.
    3. Muramatsu, Masakuni & Irie, Tunemasa & Nagatani, Takashi, 1999. "Jamming transition in pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 267(3), pages 487-498.
    4. Dirk Helbing & Joachim Keltsch & Péter Molnár, 1997. "Modelling the evolution of human trail systems," Nature, Nature, vol. 388(6637), pages 47-50, July.
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    Cited by:

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    2. Li, Xiang & Sun, Jian-Qiao, 2016. "Effects of vehicle–pedestrian interaction and speed limit on traffic performance of intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 335-347.
    3. Suma, Yushi & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2012. "Anticipation effect in pedestrian dynamics: Modeling and experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 248-263.
    4. Li, Xiang & Sun, Jian-Qiao, 2015. "Studies of vehicle lane-changing to avoid pedestrians with cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 251-271.

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