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Trajectory-based analysis on pedestrian merging flow on a stair landing

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Listed:
  • Ye, Rui
  • Wang, Qiao
  • Zeng, Guang
  • Huang, Zhongyi
  • Gao, Yan
  • Fang, Zhiming

Abstract

The merging flow happens when pedestrians coming from the stair (referred to as stair crowd) encounter those coming from the floor (referred to as floor crowd) on the stair landing, which is usually thought to significantly reduce movement efficiency during building evacuation. However, currently investigations on it are still rare especially the experimental ones with trajectories. In this paper, characteristics of stair landing merging flow are analyzed, based on precise trajectories extracted from the heads through a controlled experiment. Due to the interference of floor crowd, the average path of stair crowd in merging flow experiment is less smooth, compared with that in experiment with no merging flow. Pedestrian total travel time and total travel distance on the stair landing exhibit a linear relation, but the fitting functions are varied depending on the movement directions (ascent and descent), merging conditions (with and without merging flow), and crowd types (floor crowd and stair crowd). The sum of flow rates for stair crowd and floor crowd before merging is larger than the flow rate of overall crowd after merging, due to the occurrence of congestion after merging. Microscopic fundamental diagrams based on Voronoi diagram for different movements are derived and compared. For movements without merging flow, the speed on the stair landing is higher during descent movement. While for movements with merging flow, the speed on the stair landing is higher during ascent movement, which results from the higher speed for ascent floor crowd because ascent floor crowd is not affected by the transition from stair to landing when just stepping onto the stair landing and is less affected by the merging phenomenon.

Suggested Citation

  • Ye, Rui & Wang, Qiao & Zeng, Guang & Huang, Zhongyi & Gao, Yan & Fang, Zhiming, 2022. "Trajectory-based analysis on pedestrian merging flow on a stair landing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    • Handle: RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122005532
    DOI: 10.1016/j.physa.2022.127853
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    References listed on IDEAS

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    1. Zahra Shahhoseini & Majid Sarvi, 2017. "Collective movements of pedestrians: How we can learn from simple experiments with non-human (ant) crowds," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-20, August.
    2. Shahhoseini, Zahra & Sarvi, Majid, 2019. "Pedestrian crowd flows in shared spaces: Investigating the impact of geometry based on micro and macro scale measures," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 57-87.
    3. Steffen, B. & Seyfried, A., 2010. "Methods for measuring pedestrian density, flow, speed and direction with minimal scatter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1902-1910.
    4. Liang, Mengdi & Xu, Jie & Jia, Limin & Qin, Yong, 2020. "An improved model of passenger merging in a Y-shaped passage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
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