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Anticipation effect in pedestrian dynamics: Modeling and experiments

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  • Suma, Yushi
  • Yanagisawa, Daichi
  • Nishinari, Katsuhiro

Abstract

In this paper, we propose the anticipation floor field (AFF) as an extension of the floor field (FF) model, which is one of the successful models in describing pedestrian dynamics. The AFF focuses on non-local interaction between pedestrians, which has not been taken into account in the FF model based on local rules. We have conducted several experiments, as well as simulations of counter flow to show the validity of our model. It is found that strength and range of anticipation significantly affect pedestrian dynamics, and there is an optimal strength of anticipation to realize the smoothest counter flow.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:1:p:248-263
    DOI: 10.1016/j.physa.2011.07.022
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    Cited by:

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    3. Huang, Rong & Zhao, Xuan & Zhou, Chenyu & Kong, Lingchen & Liu, Chengqing & Yu, Qiang, 2022. "Static floor field construction and fine discrete cellular automaton model: Algorithms, simulations and insights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    4. Yamamoto, Hiroki & Yanagisawa, Daichi & Feliciani, Claudio & Nishinari, Katsuhiro, 2019. "Body-rotation behavior of pedestrians for collision avoidance in passing and cross flow," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 486-510.
    5. Feliciani, Claudio & Nishinari, Katsuhiro, 2016. "An improved Cellular Automata model to simulate the behavior of high density crowd and validation by experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 135-148.
    6. Cui, Geng & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2021. "Incorporating genetic algorithm to optimise initial condition of pedestrian evacuation based on agent aggressiveness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    7. Xiao, Tianyi & Mu, Tong & Shen, Sunle & Song, Yiming & Yang, Shufan & He, Jie, 2022. "A dynamic physical-distancing model to evaluate spatial measures for prevention of Covid-19 spread," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    8. Fang, Shuyi & Jin, Cheng-Jie & Jiang, Rui & Li, Dawei, 2024. "Simulating the bi-directional pedestrian flow under high densities by a floor field cellular automaton model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    9. Yang, Junheng & Zang, Xiaodong & Chen, Weiying & Luo, Qiang & Wang, Rui & Liu, Yuanqian, 2024. "Improved social force model based on pedestrian collision avoidance behavior in counterflow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 642(C).
    10. Pereira, L.A. & Burgarelli, D. & Duczmal, L.H. & Cruz, F.R.B., 2017. "Emergency evacuation models based on cellular automata with route changes and group fields," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 97-110.
    11. Kaji, Masaru & Inohara, Takehiro, 2017. "Cellular automaton simulation of unidirectional pedestrians flow in a corridor to reproduce the unique velocity profile of Hagen–Poiseuille flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 85-95.
    12. Jinrui Liu & Maosheng Li & Panpan Shu, 2021. "Subdivided Cellular Automata Model Considering Anticipation Floor Field and Analysis of Pedestrian Detour Behavior," Sustainability, MDPI, vol. 13(19), pages 1-25, September.
    13. Tao, Y.Z. & Dong, L.Y., 2017. "A Cellular Automaton model for pedestrian counterflow with swapping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 155-168.
    14. Guo, Wei & Wang, Xiaolu & Zheng, Xiaoping, 2015. "Lane formation in pedestrian counterflows driven by a potential field considering following and avoidance behaviours," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 87-101.
    15. Cirillo, Emilio N.M. & Muntean, Adrian, 2013. "Dynamics of pedestrians in regions with no visibility— A lattice model without exclusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3578-3588.
    16. Cui, Geng & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2023. "Learning from experimental data to simulate pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    17. 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.

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