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Author:

Li, Y. (Li, Y..) | Zhang, Y. (Zhang, Y..) (Scholars:张勇) | Liu, H. (Liu, H..) | Ge, Q. (Ge, Q..)

Indexed by:

Scopus PKU CSCD

Abstract:

In view of the characteristics of crowd movement in rail transit, a navigation field is introduced on the traditional social force model to build a crowd simulation system, in which the social force model is responsible for the interaction of pedestrian with pedestrians and the environment around them, while the navigation field is responsible for the pedestrian's path planning in the rail transit. Compared with the traditional social force model, it is possible to avoid the "jitter" or the local congestion caused by the unreasonable setting of the intermediate target point. Based on the above, a crowd simulation system is developed for rail transit and the Beijing Zoo Subway Station is used as experimental scenario. The experimental results show that there is no "jitter" or partial congestion during the simulation. This method is suitable for crowd simulation in rail transit. © 2018, Editorial Department of Journal of Beijing Jiaotong University. All right reserved.

Keyword:

Crowd simulation; Navigation field; Rail transit; Social force model

Author Community:

  • [ 1 ] [Li, Y.]Multimedia and Intelligent Software Technology Laboratory, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zhang, Y.]Multimedia and Intelligent Software Technology Laboratory, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Zhang, Y.]Beijing Transportation Information Center, Beijing, 100161, China
  • [ 4 ] [Liu, H.]Beijing Transportation Information Center, Beijing, 100161, China
  • [ 5 ] [Ge, Q.]Beijing Transportation Information Center, Beijing, 100161, China

Reprint Author's Address:

  • 张勇

    [Zhang, Y.]Multimedia and Intelligent Software Technology Laboratory, Beijing University of TechnologyChina

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Source :

Journal of Beijing Jiaotong University

ISSN: 1673-0291

Year: 2018

Issue: 5

Volume: 42

Page: 130-134

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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