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A cell-based study on pedestrian acceleration and overtaking in a transfer station corridor

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  • Ji, Xiangfeng
  • Zhou, Xuemei
  • Ran, Bin

Abstract

Pedestrian speed in a transfer station corridor is faster than usual and sometimes running can be found among some of them. In this paper, pedestrians are divided into two categories. The first one is aggressive, and the other is conservative. Aggressive pedestrians weaving their way through crowd in the corridor are the study object of this paper. During recent decades, much attention has been paid to the pedestrians’ behavior, such as overtaking (also deceleration) and collision avoidance, and that continues in this paper. After sufficiently analyzing the characteristics of pedestrian flow in transfer station corridor, a cell-based model is presented in this paper, including the acceleration (also deceleration) and overtaking analysis. Acceleration (also deceleration) in a corridor is fixed according to Newton’s Law and then speed calculated with a kinematic formula is discretized into cells based on the fuzzy logic. After the speed is updated, overtaking is analyzed based on updated speed and force explicitly, compared to rule-based models, which herein we call implicit ones. During the analysis of overtaking, a threshold value to determine the overtaking direction is introduced. Actually, model in this paper is a two-step one. The first step is to update speed, which is the cells the pedestrian can move in one time interval and the other is to analyze the overtaking. Finally, a comparison between the rule-based cellular automata, the model in this paper and data in HCM 2000 is made to demonstrate our model can be used to achieve reasonable simulation of acceleration (also deceleration) and overtaking among pedestrians.

Suggested Citation

  • Ji, Xiangfeng & Zhou, Xuemei & Ran, Bin, 2013. "A cell-based study on pedestrian acceleration and overtaking in a transfer station corridor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1828-1839.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:8:p:1828-1839
    DOI: 10.1016/j.physa.2012.12.016
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    References listed on IDEAS

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    Cited by:

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    2. Tang, Tie-Qiao & Xie, Chuan-Zhi & Wang, Tao & Zhang, Jian, 2019. "Modeling and simulating the matching behavior of pedestrian flow at training school during the pickup period after class," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 649-660.
    3. Fang, Shuyi & Jin, Cheng-Jie & Jiang, Rui & Li, Dawei, 2024. "Simulating the bi-directional pedestrian flow under high densities by a floor field cellular automaton model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    4. Kaji, Masaru & Inohara, Takehiro, 2017. "Cellular automaton simulation of unidirectional pedestrians flow in a corridor to reproduce the unique velocity profile of Hagen–Poiseuille flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 85-95.
    5. Shang, Pan & Li, Ruimin & Guo, Jifu & Xian, Kai & Zhou, Xuesong, 2019. "Integrating Lagrangian and Eulerian observations for passenger flow state estimation in an urban rail transit network: A space-time-state hyper network-based assignment approach," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 135-167.
    6. Xie, Chuan-Zhi & Tang, Tie-Qiao & Hu, Peng-Cheng & Chen, Liang, 2022. "Observation and cellular-automaton based modeling of pedestrian behavior on an escalator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    7. 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.
    8. Zhou, Xuemei & Hu, Jingjie & Ji, Xiangfeng & Xiao, Xiongziyan, 2019. "Cellular automaton simulation of pedestrian flow considering vision and multi-velocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 982-992.
    9. Wu, Jie & Wang, Xiuling & Chen, Jinjin & Shu, Gang & Li, Ya, 2015. "The position of a door can significantly impact on pedestrians’ evacuation time in an emergency," Applied Mathematics and Computation, Elsevier, vol. 258(C), pages 29-35.

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