Früher|Nächster

Social groups’ spatio-temporal behavior characteristics analysis in subway evacuation process based on VR digital twin experiments

  • role： First author第一作者
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • Email：huanglin@radi.ac.cn
  • Introduction：黄琳，研究方向为人群行为模拟、数字孪生应用。E-mail： huanglin@radi.ac.cn
HUANG Lin1,  
  • role： Corresponding author通信作者
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • Email：liwh@aircas.ac.cn
  • Introduction：李文航，研究方向为微观人群行为建模与模拟。E-mail： liwh@aircas.ac.cn
LI Wenhang1*,  
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 101408, China

GONG Jianhua12,  
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 101408, China

MA Haonan12,  
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 101408, China

HU Mengyu12

Resümee

The concepts of “digital twin” and “meta-universe” provide new ideas for the field of crowd behavior simulation. Using digital twin methods to conduct crowd behavior experiments to obtain data and then researching on human spatial and temporal behavior in specific scenarios have become important directions in the field of crowd simulation and indoor GIS research. Digital twin crowd behavior experiment is an innovative geographical experiment to explore crowd behavior, geographical phenomena and processes, and human-geography relationship in a real geographical environment. This paper proposes a theoretical framework for conducting digital twin experiments on crowd behavior from experimental purpose, object, process, evaluation, and results and analysis. The framework summarizes the basic theories, including geographic cognitive, similarity, scale, complexity problem, and geographic intelligence simulation theories. We also summarize the experimental principles of digital twin crowd behavior, such as experimental similarity, collaboration and heterogeneity, and standardization and normalization. Furthermore, we propose the content and classification of experiments on digital twin crowd evacuation. On the basis of this theoretical framework, a VR-based social group evacuation digital twin experiment is conducted in the Olympic Park Station. The spatial structure and evacuation behavior of social groups are qualitatively and quantitatively analyzed using experimental data. We evaluate the spatial structure characteristics of two- and three-member social groups, the characteristics of the angle and distance between social group members, the information diffusion way within social group members, and the evacuation and eye-tracking point trajectories of social groups. Results show that during the evacuation process, social group members exhibit V and “side-by-side” structures. They maintain a compact spatial structure in an emergency, indicating that group members have the desire to find a safe exit together, and this willingness has a crucial effect on crowd evacuation behavior. In some special areas such as stairs and escalators, the spatial structures of social groups have significant changes. They show a tendency to improve the walking speed through these areas as soon as possible rather than to maintain the compact spatial structures. The angle between the facing direction of an evacuee and that of other social group members is less than 60°, and smaller distances and information diffusion interactions among social group members significantly improve the evacuation efficiency. The analysis of the evacuation and eye-tracking point trajectories in the digital twin scenario reveals that the evacuating crowd interacts considerably with pillars, exits, and transfer channels, indicating a great need for direction information in these areas. Optimizing an evacuation sign system in these key areas can greatly improve the evacuation efficiency. The above findings on crowd behavior are of great significance to crowd behavior modeling, and the digital twin experiment results can identify bottleneck areas in the subway station selected in this study, providing optimization suggestions for layout design and emergency plans. The ability of subway station managers to predict and respond to emergencies can be further strengthened. The results of this study have important practical application value to reduce personal and property losses in disaster events.

Schlüsselwort

remote sensing;digital twin;crowd behavior experiment;subway evacuation;social groups;interactive behavior

References

  1. 1.
    Arias S, La Mendola S, Wahlqvist J, Rios O, Nilsson D and Ronchi E. 2019. Virtual reality evacuation experiments on way-finding systems for the future circular collider. Fire Technology, 55(6): 2319-2340
  2. 2.
    Bai H, Yang S, Feng X J, Song X M and Dong S F. 2021. Simulation research on passenger flow evacuation in rail transit station based on BIM-VR. Urban Rapid Rail Transit, 34(5): 60-65
  3. 3.
    Bernardes S M F, Rebelo F, Vilar E, Noriega P and Borges T. 2015. Methodological approaches for use virtual reality to develop emergency evacuation simulations for training, in emergency situations. Procedia Manufacturing, 3: 6313-6320
  4. 4.
    Cao L J, Lin J and Li N. 2019. A virtual reality based study of indoor fire evacuation after active or passive spatial exploration. Computers in Human Behavior, 90: 37-45
  5. 5.
    Feng Z N, González V A, Amor R, Lovreglio R and Cabrera-Guerrero G. 2018. Immersive virtual reality serious games for evacuation training and research: a systematic literature review. Computers and Education, 127: 252-266
  6. 6.
    Guo Y K, Zhu J, Wang Y, Chai J C, Li W L, Fu L, Xu B L and Gong Y H. 2020. A virtual reality simulation method for crowd evacuation in a multiexit indoor fire environment. ISPRS International Journal of Geo-Information, 9(12): 750
  7. 7.
    Hu M and Liu B W. 2018. VR-based tunnel fire evacuation commander training system. China Safety Science Journal, 28(5): 185-190
  8. 8.
    Huang L, Gong J H, Li W H, Xu T, Shen S, Liang J M, Feng Q L, Zhang D and Sun J. 2018. Social force model-based group behavior simulation in virtual geographic environments. ISPRS International Journal of Geo-Information, 7(2): 79
  9. 9.
    Huang L, Gong J H and Li W H. 2021. A perception model for optimizing and evaluating evacuation guidance systems. ISPRS International Journal of Geo-Information, 10(2): 54
  10. 10.
    Li R F, Dong S F, Wang Z J and Wang A L. 2021. Research and implementation of metro emergency evacuation simulation system based on VR. Railway Computer Application, 30(6): 68-73
  11. 11.
    Li W H, Gong J H, Huang L and Ma H N. 2024. Digital twins of micro crowd: The concept, framwork, and methods. National Remote Sensing Bulletin, 28(5): 1295-1313
  12. 12.
    Lin J, Zhu R H, Li N and Becerik-Gerber B. 2020. Do people follow the crowd in building emergency evacuation? A cross-cultural immersive virtual reality-based study. Advanced Engineering Informatics, 43: 101040
  13. 13.
    Lovreglio R, Dillies E, Kuligowski E, Rahouti A and Haghani M. 2021. Investigating exit choice in built environment evacuation combining immersive virtual reality and discrete choice modelling. arXiv: 2110.11577
  14. 14.
    Ma X H, Zhou J P, Gong J H, Huang L, Li W H and Zou Y L. 2019. VR eye-tracking perception experiment and layout evaluation for indoor emergency evacuation signs. Journal of Geo-Information Science, 21(8): 1170-1182
  15. 15.
    Moussaïd M, Perozo N, Garnier S, Helbing D and Theraulaz G. 2010. The walking behaviour of pedestrian social groups and its impact on crowd dynamics. PLoS ONE, 5(4): e10047
  16. 16.
    Snopková D, Ugwitz P, Stachoň Z, Hladík J, Juřík V, Kvarda O and Kubíček P. 2022. Retracing evacuation strategy: a virtual reality game-based investigation into the influence of building’s spatial configuration in an emergency. Spatial Cognition and Computation, 22(1/2): 30-50
  17. 17.
    Wang Y, Zhang J B, Zhu J and Zhang Y C. 2023. VR simulation method for emergency evacuation in subway station fire based on improved social force model. Journal of Safety Science and Technology, 19(5): 194-201
  18. 18.
    Wang Z W, Ma W B and Wang Z H. 2022a. Development and application of immersive evacuation drill system for underground high speed railway station based on BIM and VR technology. Railway Engineering, 62(9): 131-135, 140
  19. 19.
    Wang Z W, Ma W B, Yu J J and Guan G S. 2022b. Key technologies for evacuation drill scene construction of immersive underground high speed railway station based on BIM+VR. Railway Engineering, 62(12): 153-157
  20. 20.
    Zhang D, Gong J H, Li W H, Yi Z H, Shen S and Huang L. 2019. A comparative analysis of virtual and real trajectories of social groups. Geography and Geo-Information Science, 35(3): 21-27
  21. 21.
    Zhang F, Hu M Y, Che W T, Lin H and Fang C Y. 2018. Framework for virtual cognitive experiment in virtual geographic environments. ISPRS International Journal of Geo-Information, 7(1): 36
  22. 22.
    Zhang L. 2021. Eevacuation simulation method of large space cabin under 3D VR technology. Ship Science and Technology, 43(22): 10-12
  23. 23.
    Zhang L, Zhu G Q and Guo D G. 2015. Study on fire escape training system base on VR. Fire Science and Technology, 34(4): 526-529
  24. 24.
    Zhang M, Ke J J, Tong L Y and Luo X W. 2021. Investigating the influence of route turning angle on compliance behaviors and evacuation performance in a virtual-reality-based experiment. Advanced Engineering Informatics, 48: 101259

Lesen Sie die ganze Passage

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website