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Simulation of pedestrian counter-flow with right-moving preference

Author

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  • Yang, Lizhong
  • Li, Jian
  • Liu, Shaobo

Abstract

People prefer to walk on the right-hand side of the road for physical and social reasons. In this paper, pedestrian counter-flow in a channel is simulated with the Cellular Automata (CA) Model, with focus on right-preference. Two types of pedestrians are taken into account, walking leftward and rightward along the channel. Circular and open boundaries are adopted respectively. The right-preference intensity, k, is introduced, defined as the ratio of the right-moving probability to left-moving probability. In simulations, the dynamical transition between fluid and jammed phase is presented. With a fixed k, the critical density is independent of the channel size. According to research results on physiology and sociology [O. Guentuerkuen, Nature 421 (2003) 711; M. Reiss, G. Reiss, Percept. Mot. Skill 85 (1997) 569; M.C. Corballis, Psychol. Rev. 104 (1997) 714], k=1,2,8 have been discussed, and k=8 is satisfied in this work. Furthermore, simulation results are compared with the ideal calculation, and other researchers’ experiments [M. Isobe, T. Adachi, T. Nagatani, Physica A 336 (2004) 638]. It is found that right-preference is effective when the density is below critical. The model is shown to be useful to simulate and analyze this situation numerically.

Suggested Citation

  • Yang, Lizhong & Li, Jian & Liu, Shaobo, 2008. "Simulation of pedestrian counter-flow with right-moving preference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3281-3289.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:13:p:3281-3289
    DOI: 10.1016/j.physa.2008.01.107
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    Citations

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    Cited by:

    1. Cao, Shuchao & Song, Weiguo & Lv, Wei & Fang, Zhiming, 2015. "A multi-grid model for pedestrian evacuation in a room without visibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 45-61.
    2. Sun, Yi, 2020. "Kinetic Monte Carlo simulations of bi-direction pedestrian flow with different walk speeds," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    3. Tianran Han & Jianming Zhao & Wenquan Li, 2020. "Smart-Guided Pedestrian Emergency Evacuation in Slender-Shape Infrastructure with Digital Twin Simulations," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    4. Ma, Jian & Song, Wei-guo & Zhang, Jun & Lo, Siu-ming & Liao, Guang-xuan, 2010. "k-Nearest-Neighbor interaction induced self-organized pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2101-2117.
    5. Sun, Yi, 2019. "Simulations of bi-direction pedestrian flow using kinetic Monte Carlo methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 519-531.
    6. 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).
    7. Gabriele Montecchiari & Gabriele Bulian & Paolo Gallina, 2018. "Towards real-time human participation in virtual evacuation through a validated simulation tool," Journal of Risk and Reliability, , vol. 232(5), pages 476-490, October.
    8. Liu, Yulu & Ma, Xuechen & Tao, Yizhou & Dong, Liyun & Ding, Xu & Qiu, Xiang, 2024. "Numerical investigation on the impact of obstacles on phase transition in pedestrian counter-flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    9. Zeng, Yiping & Ye, Rui & Song, Weiguo & Luo, Shengfeng & Meng, Fanyu & Vizzari, Giuseppe, 2021. "Entropy analysis of the laminar movement in bidirectional pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    10. Leng, Biao & Wang, Jianyuan & Zhao, Wenyuan & Xiong, Zhang, 2014. "An extended floor field model based on regular hexagonal cells for pedestrian simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 119-133.
    11. Li, Xingli & Guo, Fang & Kuang, Hua & Zhou, Huaguo, 2017. "Effect of psychological tension on pedestrian counter flow via an extended cost potential field cellular automaton model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 47-57.
    12. Leng, Biao & Wang, Jianyuan & Xiong, Zhang, 2015. "Pedestrian simulations in hexagonal cell local field model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 532-543.
    13. Fang, Jun & Qin, Zheng & Hu, Hao & Xu, Zhaohui & Li, Huan, 2012. "The fundamental diagram of pedestrian model with slow reaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6112-6120.
    14. Zhang, Dawei & Zhu, Haitao & Hostikka, Simo & Qiu, Shi, 2019. "Pedestrian dynamics in a heterogeneous bidirectional flow: Overtaking behaviour and lane formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 72-84.
    15. 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.

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