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Pedestrian dynamics of single-file experiments with music considering different music and different instructions

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  • Zeng, Guang
  • Zhang, Jun
  • Ye, Rui
  • Cao, Shuchao
  • Song, Weiguo

Abstract

Pedestrian crowds are common in public facilities. It is essential to manage pedestrian flow for the safety of pedestrians. The rhythm is a potential method for improving pedestrian flow. Here we studied pedestrian dynamics with music by a series of single-file experiments considering different kinds of music (motivational music and nonmotivational music) and different instructions (listen to the music while walking, follow the beat of the music). To observe the effect of music on pedestrian movement, the condition without any rhythm and that with music were connected without breaking in a same run. Trajectories of the pedestrians were extracted and further analyzed. It is found that the effect of music on pedestrian flow can be observed directly. Both different kinds of music and different instructions can influence pedestrian motion. Pedestrians walk more quickly with the motivational music at all densities when instructed to listen to the music while walking. While they will walk more slowly at low density and more quickly at high density with the nonmotivational music. But when the participants are asked to follow the music, the velocity of pedestrians is only influenced by the music at high density. Comparing fundamental diagrams, we found that the music can improve pedestrian flow at most conditions. Our study will be helpful for understanding the effect of music on pedestrian dynamics.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:phsmap:v:594:y:2022:i:c:s0378437121009882
    DOI: 10.1016/j.physa.2021.126825
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    References listed on IDEAS

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    1. Ujjal Chattaraj & Armin Seyfried & Partha Chakroborty, 2009. "Comparison Of Pedestrian Fundamental Diagram Across Cultures," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 393-405.
    2. Cao, Shuchao & Lian, Liping & Chen, Mingyi & Yao, Ming & Song, Weiguo & Fang, Zhiming, 2018. "Investigation of difference of fundamental diagrams in pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 661-670.
    3. 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).
    4. Fu, Zhijian & Li, Tao & Deng, Qiangqiang & Schadschneider, Andreas & Luo, Lin & Ma, Jian, 2021. "Effect of turning curvature on the single-file dynamics of pedestrian flow: An experimental study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
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    Cited by:

    1. Fu, Libi & Chen, Yunqian & Qin, Huigui & Chen, Qiyi & He, Yangjian & Shi, Yongqian, 2023. "Dynamics of merging flow involving luggage-laden pedestrians in a Y-shaped corridor: An experimental study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    2. 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).
    3. 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).
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    5. 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).

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