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Traffic Instabilities in Self-Organized Pedestrian Crowds

Author

Listed:
  • Mehdi Moussaïd
  • Elsa G Guillot
  • Mathieu Moreau
  • Jérôme Fehrenbach
  • Olivier Chabiron
  • Samuel Lemercier
  • Julien Pettré
  • Cécile Appert-Rolland
  • Pierre Degond
  • Guy Theraulaz

Abstract

In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds. Author Summary: A crowd of pedestrians is a complex system that exhibits a rich variety of self-organized collective behaviours. For instance, when two flows of people are walking in opposite directions in a crowded street, pedestrians spontaneously share the available space by forming lanes of uniform walking directions. This “pedestrian highway” is a typical example of self-organized functional pattern, as it increases the traffic efficiency with no need of external control. In this work, we have conducted a series of laboratory experiments to determine the behavioral mechanisms underlying this pattern. In contrast to previous theoretical predictions, we found that the traffic organization actually alternates in time between well-organized and disorganized states. Our results demonstrate that this unstable dynamics is due to interactions between people walking faster and slower than the average speed of the crowd. While the traffic efficiency is maximized when everybody walks at the same speed, crowd heterogeneity reduces the collective benefits provided by the traffic segregation. This work is a step ahead in understanding the mechanisms of crowd self-organization, and opens the way for the elaboration of management strategies bound to promote smart collective behaviors.

Suggested Citation

  • Mehdi Moussaïd & Elsa G Guillot & Mathieu Moreau & Jérôme Fehrenbach & Olivier Chabiron & Samuel Lemercier & Julien Pettré & Cécile Appert-Rolland & Pierre Degond & Guy Theraulaz, 2012. "Traffic Instabilities in Self-Organized Pedestrian Crowds," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-10, March.
  • Handle: RePEc:plo:pcbi00:1002442
    DOI: 10.1371/journal.pcbi.1002442
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    References listed on IDEAS

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    Cited by:

    1. Guo, Ning & Jiang, Rui & Wong, S.C. & Hao, Qing-Yi & Xue, Shu-Qi & Xiao, Yao & Wu, Chao-Yun, 2020. "Modeling the interactions of pedestrians and cyclists in mixed flow conditions in uni- and bidirectional flows on a shared pedestrian-cycle road," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 259-284.
    2. Femke van Wageningen-Kessels & Winnie Daamen & Serge P. Hoogendoorn, 2018. "Two-Dimensional Approximate Godunov Scheme and What It Means For Continuum Pedestrian Flow Models," Transportation Science, INFORMS, vol. 52(3), pages 547-563, June.
    3. Saberi, Meead & Aghabayk, Kayvan & Sobhani, Amir, 2015. "Spatial fluctuations of pedestrian velocities in bidirectional streams: Exploring the effects of self-organization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 120-128.
    4. Goldsztein, Guillermo H., 2017. "Crowd of individuals walking in opposite directions. A toy model to study the segregation of the group into lanes of individuals moving in the same direction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 162-173.
    5. Lian, Liping & Song, Weiguo & Yuen, Kwok Kit Richard & Telesca, Luciano, 2018. "Investigating the time evolution of some parameters describing inflow processes of pedestrians in a room," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 77-88.
    6. 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.
    7. Ye, Rui & Lian, Liping & Zeng, Yiping, 2024. "A quantitative analysis on bidirectional pedestrian flows through angled corridors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    8. Jonathan B Dingwell & Joseph P Cusumano, 2019. "Humans use multi-objective control to regulate lateral foot placement when walking," PLOS Computational Biology, Public Library of Science, vol. 15(3), pages 1-28, March.
    9. Zeng, Tian & Wei, Yidong & Hu, Zuoan & Ma, Yi, 2023. "Comparison study in single-file pedestrian flow dynamics: Foot motion perspective versus head motion perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    10. 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.
    11. 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).

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