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An Improved Social Force Model of Pedestrian Twice–Crossing Based on Spatial–Temporal Trajectory Characteristics

Author

Listed:
  • Siyuan Ma

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Yongqing Guo

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Fulu Wei

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Qingyin Li

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Zhenyu Wang

    (Center for Urban Transportation Research, University of South Florida, Tampa, FL 33620, USA)

Abstract

Pedestrian two-stage crossing, as one of the key elements of the urban roadway network, affects not only vehicle flow at signalized interactions, but also road capacities in the transport system. Therefore, it is vital to deeply understand the behavioral characteristics of pedestrian twice-crossing in order to improve the safety and efficiency of the road transport network. Based on our previous study, this study continues to improve the social force model by classifying the trajectory type of pedestrian twice crossing. In the interactive aggregation, the pedestrian trajectory line was divided into two types: straight path and curved path. The Work–Energy Principle and Impulse–Momentum Principle were used to identify the spatial and temporal characteristics of pedestrian twice-crossing behaviors. It was found that when pedestrians on the two sides are facing very close in a congested section, the maximum repulsive force appears to be a dramatic increase and remains for a period of time. This result provides us with direction for updating the social force model, focusing on the repulsive force generated by the opposite flow. The improved model can achieve high precision in predicting pedestrian twice-crossing behaviors. The findings of this study have great implications for designing pedestrian facilities and optimizing pedestrian signal timings, thus helping to increase the mobility and safety of pedestrian twice-crossing.

Suggested Citation

  • Siyuan Ma & Yongqing Guo & Fulu Wei & Qingyin Li & Zhenyu Wang, 2022. "An Improved Social Force Model of Pedestrian Twice–Crossing Based on Spatial–Temporal Trajectory Characteristics," Sustainability, MDPI, vol. 14(24), pages 1-14, December.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16615-:d:1000718
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    References listed on IDEAS

    as
    1. Juan Wei & Wenjie Fan & Yangyong Guo & Jun Hu & Yuanyuan Fang, 2020. "An extended social force model for pedestrian evacuation under disturbance fluctuation force," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(07), pages 1-13, July.
    2. Yang, Xiaoli & Yang, Xiaoxia & Li, Yongxing & Zhang, Jihui & Kang, Yuanlei, 2021. "Obstacle avoidance in the improved social force model based on ant colony optimization during pedestrian evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    3. Liang, Haoyang & Du, Jie & Wong, S.C., 2021. "A Continuum model for pedestrian flow with explicit consideration of crowd force and panic effects," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 100-117.
    4. Kang, Zengxin & Zhang, Lei & Li, Kun, 2019. "An improved social force model for pedestrian dynamics in shipwrecks," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 355-362.
    5. Liu, Qian, 2018. "A social force model for the crowd evacuation in a terrorist attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 315-330.
    6. Yongqing Guo & Siyuan Ma & Fulu Wei & Liqun Lu & Feng Sun & Jie Wang, 2022. "Analysis of Behavior Characteristics for Pedestrian Twice-Crossing at Signalized Intersections Based on an Improved Social Force Model," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    Full references (including those not matched with items on IDEAS)

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