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Animal dynamics based approach for modeling pedestrian crowd egress under panic conditions

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  • Shiwakoti, Nirajan
  • Sarvi, Majid
  • Rose, Geoff
  • Burd, Martin

Abstract

Collective movement is important during emergencies such as natural disasters or terrorist attacks, when rapid egress is essential for escape. The development of quantitative theories and models to explain and predict the collective dynamics of pedestrians has been hindered by the lack of complementary data under emergency conditions. Collective patterns are not restricted to humans, but have been observed in other non-human biological systems. In this study, a mathematical model for crowd panic is derived from collective animal dynamics. The development and validation of the model is supported by data from experiments with panicking Argentine ants (Linepithema humile). A first attempt is also made to scale the model parameters for collective pedestrian traffic from those for ant traffic, by employing a scaling concept approach commonly used in biology.

Suggested Citation

  • Shiwakoti, Nirajan & Sarvi, Majid & Rose, Geoff & Burd, Martin, 2011. "Animal dynamics based approach for modeling pedestrian crowd egress under panic conditions," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1433-1449.
    • Handle: RePEc:eee:transb:v:45:y:2011:i:9:p:1433-1449
    DOI: 10.1016/j.trb.2011.05.016
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    References listed on IDEAS

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    Cited by:

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    2. Chen, Changkun & Sun, Huakai & Lei, Peng & Zhao, Dongyue & Shi, Congling, 2021. "An extended model for crowd evacuation considering pedestrian panic in artificial attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    3. Chraibi, Mohcine & Ensslen, Tim & Gottschalk, Hanno & Saadi, Mohamed & Seyfried, Armin, 2016. "Assessment of models for pedestrian dynamics with functional principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 475-489.
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    5. Xiaohong Li & Jianan Zhou & Feng Chen & Zan Zhang, 2018. "Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis," Sustainability, MDPI, vol. 10(2), pages 1-16, February.
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    8. Lin, Peng & Ma, Jian & Liu, Tianyang & Ran, Tong & Si, Youliang & Li, Tao, 2016. "An experimental study of the “faster-is-slower” effect using mice under panic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 157-166.
    9. Shi, Xiaomeng & Ye, Zhirui & Shiwakoti, Nirajan & Tang, Dounan & Lin, Junkai, 2019. "Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 350-364.
    10. Lin, Peng & Ma, Jian & Liu, Tian Yang & Ran, Tong & Si, You Liang & Wu, Fan Yu & Wang, Guo Yuan, 2017. "An experimental study of the impact of an obstacle on the escape efficiency by using mice under high competition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 228-242.
    11. Shiwakoti, Nirajan & Sarvi, Majid, 2013. "Understanding pedestrian crowd panic: a review on model organisms approach," Journal of Transport Geography, Elsevier, vol. 26(C), pages 12-17.
    12. Ning Ding, 2020. "The effectiveness of evacuation signs in buildings based on eye tracking experiment," 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. 103(1), pages 1201-1218, August.
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    14. Ma, Wanjing & Li, Li & Wang, Yinhai, 2016. "A driving force model for non-strict priority crossing behaviors of right-turn driversAuthor-Name: Lin, Dianchao," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 230-244.
    15. Haghani, Milad & Sarvi, Majid, 2017. "Social dynamics in emergency evacuations: Disentangling crowd’s attraction and repulsion effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 24-34.
    16. Nicolas, Alexandre & Bouzat, Sebastián & Kuperman, Marcelo N., 2017. "Pedestrian flows through a narrow doorway: Effect of individual behaviours on the global flow and microscopic dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 30-43.
    17. Shi, Xiaomeng & Xue, Shuqi & Feliciani, Claudio & Shiwakoti, Nirajan & Lin, Junkai & Li, Dawei & Ye, Zhirui, 2021. "Verifying the applicability of a pedestrian simulation model to reproduce the effect of exit design on egress flow under normal and emergency conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    18. Li, Wenhang & Gong, Jianhua & Yu, Ping & Shen, Shen & Li, Rong & Duan, Qishen, 2014. "Simulation and analysis of individual trampling risk during escalator transfers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 119-133.
    19. Haghani, Milad & Sarvi, Majid, 2018. "Crowd behaviour and motion: Empirical methods," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 253-294.
    20. Kayvan Aghabayk & Kiarash Radmehr & Nirajan Shiwakoti, 2020. "Effect of Intersecting Angle on Pedestrian Crowd Flow under Normal and Evacuation Conditions," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    21. Yu, Hang & Li, Xintong & Song, Weiguo & Zhang, Jun & Li, Xudong & Xu, Han & Jiang, Kechun, 2022. "Pedestrian emergency evacuation model based on risk field under attack event," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    22. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
    23. 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.
    24. Huang, Zhiren & Wang, Pu & Zhang, Fan & Gao, Jianxi & Schich, Maximilian, 2018. "A mobility network approach to identify and anticipate large crowd gatherings," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 147-170.
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