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Continuum modelling of pedestrian flows: From microscopic principles to self-organised macroscopic phenomena

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  • Hoogendoorn, Serge P.
  • van Wageningen-Kessels, Femke L.M.
  • Daamen, Winnie
  • Duives, Dorine C.

Abstract

The dynamics of pedestrian flows can be captured in a continuum modelling framework. However, compared to vehicular flow, this is a much more challenging task. In particular the integration of flow propagation and path choice are known to be problematic. Furthermore, pedestrian flow is characterised by different self-organised phenomena, such as the formation of dynamic lanes and diagonal stripes, which have not yet been captured in a continuum modelling framework.

Suggested Citation

  • Hoogendoorn, Serge P. & van Wageningen-Kessels, Femke L.M. & Daamen, Winnie & Duives, Dorine C., 2014. "Continuum modelling of pedestrian flows: From microscopic principles to self-organised macroscopic phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 684-694.
    • Handle: RePEc:eee:phsmap:v:416:y:2014:i:c:p:684-694
    DOI: 10.1016/j.physa.2014.07.050
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    References listed on IDEAS

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    Cited by:

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    5. Hänseler, Flurin S. & Bierlaire, Michel & Scarinci, Riccardo, 2016. "Assessing the usage and level-of-service of pedestrian facilities in train stations: A Swiss case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 106-123.
    6. 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.
    7. Marija Nikolić & Michel Bierlaire & Matthieu de Lapparent & Riccardo Scarinci, 2019. "Multiclass Speed-Density Relationship for Pedestrian Traffic," Transportation Science, INFORMS, vol. 53(3), pages 642-664, May.
    8. van Wageningen-Kessels, Femke & Leclercq, Ludovic & Daamen, Winnie & Hoogendoorn, Serge P., 2016. "The Lagrangian coordinate system and what it means for two-dimensional crowd flow models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 272-285.
    9. Nicholas Molyneaux & Riccardo Scarinci & Michel Bierlaire, 2021. "Design and analysis of control strategies for pedestrian flows," Transportation, Springer, vol. 48(4), pages 1767-1807, August.
    10. 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.
    11. Nicholas Molyneaux & Riccardo Scarinci & Michel Bierlaire, 0. "Design and analysis of control strategies for pedestrian flows," Transportation, Springer, vol. 0, pages 1-41.
    12. Bosina, Ernst & Weidmann, Ulrich, 2017. "Estimating pedestrian speed using aggregated literature data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 1-29.
    13. Xu, Qiancheng & Chraibi, Mohcine & Tordeux, Antoine & Zhang, Jun, 2019. "Generalized collision-free velocity model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    14. Qingyan Ning & Maosheng Li, 2022. "Modeling Pedestrian Detour Behavior By-Passing Conflict Areas," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    15. Sun, Cheng & Sun, Shi & Qu, Dagang & Zhu, Xun & Liu, Ying, 2023. "Modeling of pedestrian turning behavior and prediction of pedestrian density distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    16. Liu, Jing & Jia, Yang & Mao, Tianlu & Wang, Zhaoqi, 2022. "Modeling and simulation analysis of crowd evacuation behavior under terrorist attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    17. Nikolić, Marija & Bierlaire, Michel & Farooq, Bilal & de Lapparent, Matthieu, 2016. "Probabilistic speed–density relationship for pedestrian traffic," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 58-81.
    18. Duives, Dorine C. & Daamen, Winnie & Hoogendoorn, Serge P., 2016. "Continuum modelling of pedestrian flows — Part 2: Sensitivity analysis featuring crowd movement phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 36-48.
    19. Zhou, Zi-Xuan & Nakanishi, Wataru & Asakura, Yasuo, 2021. "Data-driven framework for the adaptive exit selection problem in pedestrian flow: Visual information based heuristics approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    20. Ji, Xiangfeng & Zhang, Jian & Hu, Yongkai & Ran, Bin, 2016. "Pedestrian movement analysis in transfer station corridor: Velocity-based and acceleration-based," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 416-434.
    21. Liu, Chi & Song, Weiguo & Fu, Libi & Lian, Liping & Lo, Siuming, 2017. "Experimental study on relaxation time in direction changing movement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 44-52.
    22. Li, Maosheng & Shu, Panpan & Xiao, Yao & Wang, Pu, 2021. "Modeling detour decision combined the tactical and operational layer based on perceived density," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    23. Bode, Nikolai W.F. & Chraibi, Mohcine & Holl, Stefan, 2019. "The emergence of macroscopic interactions between intersecting pedestrian streams," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 197-210.

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