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Behavior Evolution of Multi-Group in the Process of Pedestrian Crossing Based on Evolutionary Game Theory

Author

Listed:
  • Ran Zhang

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China)

  • Zhonghua Wei

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China)

  • Heng Gu

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China)

  • Shi Qiu

    (School of Civil Engineering, Central South University, Changsha 410083, China)

Abstract

The mixed traffic flow has an increasingly impact on the operation of urban traffic. To study the evolution law of multi-group behaviors in pedestrian crossing, we used the evolutionary game theory to establish a multi-group behavior evolution model for pedestrian crossing. The process of concern started from the risk perception and multi-group behavior choice. The evolutionary stability strategies, evolution trends, and factors affecting the evolutionary path of multi-group behaviors are discussed in this paper. This study found that evolutionary strategy equilibrium of pedestrians, drivers, and traffic managers not only relied on their own earning, but also on those of the other two groups. The factors affecting its behavior included the revenue factor and the limiting factor. Evolutionary game theory was used to analyze the multi-group interaction behavior of pedestrians, vehicle drivers, and traffic managers in the process of pedestrian crossing, as well as to analyze the behavior of traffic subjects in the process of pedestrian crossing. This paper provides a basis for decision-making for the traffic management department to manage road traffic, offering a new idea from the perspective of evolution for solving the conflict of interest at the crosswalk of the road section.

Suggested Citation

  • Ran Zhang & Zhonghua Wei & Heng Gu & Shi Qiu, 2021. "Behavior Evolution of Multi-Group in the Process of Pedestrian Crossing Based on Evolutionary Game Theory," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2009-:d:498655
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    References listed on IDEAS

    as
    1. Hyung Min Kim & Iderlina Mateo-Babiano, 2018. "Pedestrian Crossing Environments in an Emerging Chinese City: Vehicle Encountering, Seamless Walking, and Sensory Perception Perspectives," Sustainability, MDPI, vol. 10(7), pages 1-17, June.
    2. Sanghamitra Das & Charles F. Manski & Mark D. Manuszak, 2005. "Walk or wait? An empirical analysis of street crossing decisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 529-548, May.
    3. Wang, Yongjie & Shen, Binchang & Wu, Hao & Wang, Chao & Su, Qian & Chen, Wenqiang, 2021. "Modeling illegal pedestrian crossing behaviors at unmarked mid-block roadway based on extended decision field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    4. Wafaa Saleh & Monika Grigorova & Samia Elattar, 2020. "Pedestrian Road Crossing at Uncontrolled Mid-Block Locations: Does the Refuge Island Increase Risk?," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    5. Tian, Huan-huan & He, Hong-di & Wei, Yan-fang & Yu, Xue & Lu, Wei-zhen, 2009. "Lattice hydrodynamic model with bidirectional pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2895-2902.
    6. Avineri, Erel & Shinar, David & Susilo, Yusak O., 2011. "Pedestrians’ behaviour in cross walks: The effects of fear of falling and age," Working papers in Transport Economics 2011:18, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    7. Jeongyun Kim & Sehyun Tak & Michel Bierlaire & Hwasoo Yeo, 2020. "Trajectory Data Analysis on the Spatial and Temporal Influence of Pedestrian Flow on Path Planning Decision," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
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