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Study on bi-direction pedestrian flow using cellular automata simulation

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  • Yue, Hao
  • Guan, Hongzhi
  • Zhang, Juan
  • Shao, Chunfu

Abstract

A simulation of bi-direction pedestrian flow based on cellular automata (CA) will be presented from two aspects: direction split and pedestrians’ walking habit in this paper. The simulation uses Dynamic Parameters Model (DPM) to simplify tactically the decision-making process of pedestrians in their movements. A new parameter right-hand parameter is introduced to describe the pedestrians’ walking preference. The relationships of velocity–density and flow–density will be studied and analyzed. It is found that there are phase transitions at the critical density point, and the pedestrian flow shows distinctive characteristics at different phases with different relationships of velocity–density and flow–density. It is also found that direction split and pedestrians’ walking habit affect the value of critical density point and the figures of velocity–density and volume–density curves. In conclusion, the simulation can reflect and describe some pedestrian flow self-organization phenomena and transition trend of empirical pedestrian flow curves.

Suggested Citation

  • Yue, Hao & Guan, Hongzhi & Zhang, Juan & Shao, Chunfu, 2010. "Study on bi-direction pedestrian flow using cellular automata simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 527-539.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:3:p:527-539
    DOI: 10.1016/j.physa.2009.09.035
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    References listed on IDEAS

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    14. Ning Ding & Hui Zhang & Tao Chen, 2017. "Simulation-based optimization of emergency evacuation strategy in ultra-high-rise buildings," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1167-1184, December.
    15. Luo, Lin & Liu, Xiaobo & Fu, Zhijian & Ma, Jian & Liu, Fanxiao, 2020. "Modeling following behavior and right-side-preference in multidirectional pedestrian flows by modified FFCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
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    17. Moonsoo Ko & Taewan Kim & Keemin Sohn, 2013. "Calibrating a social-force-based pedestrian walking model based on maximum likelihood estimation," Transportation, Springer, vol. 40(1), pages 91-107, January.
    18. Lili Lu & Gang Ren & Wei Wang & Chen Yu & Chenzi Ding, 2013. "Exploring the Effects of Different Walking Strategies on Bi-Directional Pedestrian Flow," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-9, November.
    19. Can Liao & Kejun Zhu & Haixiang Guo & Jian Tang, 2019. "Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian-Nash Equilibrium," Complexity, Hindawi, vol. 2019, pages 1-15, January.
    20. Zhou, Xuemei & Hu, Jingjie & Ji, Xiangfeng & Xiao, Xiongziyan, 2019. "Cellular automaton simulation of pedestrian flow considering vision and multi-velocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 982-992.
    21. Zhang, Qi, 2015. "Simulation model of bi-directional pedestrian considering potential effect ahead and behind," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 335-348.
    22. Gao, Jin & Zhang, Jingjing & He, Jun & Gong, Jinghai & Zhao, Jincheng, 2020. "Experiment and simulation of pedestrian’s behaviors during evacuation in an office," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

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