IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v531y2019ics0378437119309744.html
   My bibliography  Save this article

Single-file pedestrian flow experiments under high-density conditions

Author

Listed:
  • Jin, Cheng-Jie
  • Jiang, Rui
  • Li, Ruiwen
  • Li, Dawei

Abstract

In order to investigate the mechanism of uni-directional pedestrian flow, we organize one single-file flow experiment on a ring corridor. With 203 participants, the maximum global density reaches 4ped/m. The fundamental diagrams are given, and compared with that of the single-file experiments held in other countries. We find the pedestrians’ velocities in our experiment are close to the Indian results, and larger than German results. In the time-headway distributions, the peak gradually disappears with the increase of density. At medium densities, the upstream propagation of stop-and-go waves can be observed. The calculated propagation velocity is about 0.4∼0.5 m/s. At extremely high densities, the transition between stopping state and moving state can occur, which is similar to that found in uni-directional experiments with wider system width. In these phenomena, we find there exists one critical density, which is about 3ped/m. All these results can help to learn more about the essence of single-file pedestrian flow.

Suggested Citation

  • Jin, Cheng-Jie & Jiang, Rui & Li, Ruiwen & Li, Dawei, 2019. "Single-file pedestrian flow experiments under high-density conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
  • Handle: RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119309744
    DOI: 10.1016/j.physa.2019.121718
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119309744
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.121718?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin, Cheng-Jie & Jiang, Rui & Liu, Tongfei & Li, Dawei & Wang, Hao & Liu, Xianglong, 2021. "Pedestrian dynamics with different corridor widths: Investigation on a series of uni-directional and bi-directional experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    2. Cheng-Jie Jin & Ke-Da Shi & Shu-Yi Fang, 2023. "Simulation of Single-File Pedestrian Flow under High-Density Condition by a Modified Social Force Model," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    3. Tan, Bangkun & Xuan, Chenrui & Xie, Wei & Shi, Meng & Ma, Yi, 2024. "Dynamic characteristics of the sideways movement of pedestrians: An experimental study based on single-file experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    4. Wei, Yidong & Hu, Zuoan & Zeng, Tian & Xie, Wei & Ma, Yi, 2023. "Influence of walkway slope on single-file pedestrian flow dynamics: Results from an experimental study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    5. Zeng, Guang & Zhang, Jun & Ye, Rui & Cao, Shuchao & Song, Weiguo, 2022. "Pedestrian dynamics of single-file experiments with music considering different music and different instructions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    6. Xue, Shuqi & Shiwakoti, Nirajan, 2023. "A meta-synthesis of experimental studies of pedestrian movement in single-file flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    7. Jianlin, Li & Jun, Zhang & Xuehua, Song & Hang, Yu & Xintong, Li & Saizhe, Ding & Weiguo, Song, 2024. "The validation of pedestrian trajectories during turning and obstacle avoidance in virtual environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119309744. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.