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Pedestrian movement analysis in transfer station corridor: Velocity-based and acceleration-based

Author

Listed:
  • Ji, Xiangfeng
  • Zhang, Jian
  • Hu, Yongkai
  • Ran, Bin

Abstract

In this paper, pedestrians are classified into aggressive and conservative ones by their temper. Aggressive pedestrians’ walking through crowd in transfer station corridor is analyzed. Treating pedestrians as particles, this paper uses the modified social force model (MSFM) as the building block, where forces involve self-driving force, repulsive force and friction force. The proposed model in this paper is a discrete model combining the MSFM and cellular automata (CA) model, where the updating rules of the CA are redefined with MSFM. Due to the continuity of values generated by the MSFM, we use the fuzzy logic to discretize the continuous values into cells pedestrians can move in one step. With the observation that stimulus around pedestrians influences their acceleration directly, an acceleration-based movement model is presented, compared to the generally reviewed velocity-based movement model. In the acceleration-based model, a discretized version of kinematic equation is presented based on the acceleration discretized with fuzzy logic. In real life, some pedestrians would rather keep their desired speed and this is also mimicked in this paper, which is called inertia. Compared to the simple triangular membership function, a trapezoidal membership function and a piecewise linear membership function are used to capture pedestrians’ inertia. With the trapezoidal and the piecewise linear membership function, many overlapping scenarios should be carefully handled and Dubois and Prade’s four-index method is used to completely describe the relative relationship of fuzzy quantities. Finally, a simulation is constructed to demonstrate the effect of our model.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:450:y:2016:i:c:p:416-434
    DOI: 10.1016/j.physa.2015.12.139
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    References listed on IDEAS

    as
    1. Tanimoto, Jun & Hagishima, Aya & Tanaka, Yasukaka, 2010. "Study of bottleneck effect at an emergency evacuation exit using cellular automata model, mean field approximation analysis, and game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5611-5618.
    2. 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.
    3. repec:dau:papers:123456789/5946 is not listed on IDEAS
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    Cited by:

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    2. Li, Yang & Chen, Maoyin & Zheng, Xiaoping & Dou, Zhan & Cheng, Yuan, 2020. "Relationship between behavior aggressiveness and pedestrian dynamics using behavior-based cellular automata model," Applied Mathematics and Computation, Elsevier, vol. 371(C).
    3. Chen, Jingxu & Li, Zhibin & Jiang, Hang & Zhu, Senlai & Wang, Wei, 2017. "Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 880-891.
    4. 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.
    5. 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.

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