Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Improved Social Force Model based on Navigation Points for Crowd Emergent Evacuation

  • Li, Jun (School of Electronic and Information Engineering, Ningbo University of Technology) ;
  • Zhang, Haoxiang (Robotics Institute, Ningbo University of Technology) ;
  • Ni, Zhongrui (Faculty of Information Science and Technology, Ningbo University)
  • Received : 2019.07.31
  • Accepted : 2020.01.14
  • Published : 2020.12.31
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Abstract

Crowd evacuation simulation is an important research issue for designing reasonable building layouts and planning more effective evacuation routes. The social force model (SFM) is an important pedestrian movement model, and is widely used in crowd evacuation simulations. The model can effectively simulate crowd evacuation behaviors in a simple scene, but for a multi-obstacle scene, the model could result in some undesirable problems, such as pedestrian evacuation trajectory oscillation, pedestrian stagnation and poor evacuation routing. This paper analyzes the causes of these problems and proposes an improved SFM for complex multi-obstacle scenes. The new model adds navigation points and walking shortest route principles to the SFM. Based on the proposed model, a crowd evacuation simulation system is developed, and the crowd evacuation simulation was carried out in various scenes, including some with simple obstacles, as well as those with multi-obstacles. Experiments show that the pedestrians in the proposed model can effectively bypass obstacles and plan reasonable evacuation routes.

Keywords

Acknowledgement

This paper is funded by Zhejiang Provincial Natural Science Foundation of China (No. LY18F010020), and Zhejiang Provincial Natural Science Foundation of China (No. LY19F010001), and Zhejiang Provincial Education Department Foundation of China (No. Y201224456).

References

  1. D. Helbing and P. Molnar, "Social force model for pedestrian dynamics," Physical Review E, vol. 51, no. 5, pp. 4282-4286, 1995. https://doi.org/10.1103/PhysRevE.51.4282
  2. D. Helbing, A. Johansson, and H. Z. Al-Abideen, "Dynamics of crowd disasters: an empirical study," Physical Review E, vol. 75, no. 4, article no. 046109, 2007.
  3. Y. Q. Jiang, B. K. Chen, B. H. Wang, W. F. Wong, and B. Y. Cao, "Extended social force model with a dynamic navigation field for bidirectional pedestrian flow," Frontiers of Physics, vol. 12, no. 5, article no. 124502, 2017.
  4. N. Cao, Z. Qu, Y. Chen, L. Zhao, X. Song, and Q. Bai, "Destination and route choice models for bidirectional pedestrian flow based on the social force model," IET Intelligent Transport Systems, vol. 11, no. 9, pp. 537-545, 2017. https://doi.org/10.1049/iet-its.2016.0333
  5. H. Zhang, H. Liu, X. Qin, and B. Liu, "Modified two-layer social force model for emergency earthquake evacuation," Physica A: Statistical Mechanics and its Applications, vol. 492, pp. 1107-1119, 2018. https://doi.org/10.1016/j.physa.2017.11.041
  6. T. Korecki, D. Palka, and J. Was, "Adaptation of social force model for simulation of downhill skiing," Journal of Computational Science, vol. 16, pp. 29-42, 2016. https://doi.org/10.1016/j.jocs.2016.02.006
  7. W. Zeng, P. Chen, H. Nakamura, and M. Iryo-Asano, "Application of social force model to pedestrian behavior analysis at signalized crosswalk," Transportation Research Part C: Emerging Technologies, vol. 40, pp. 143-159, 2014. https://doi.org/10.1016/j.trc.2014.01.007
  8. L. Hou, J. G. Liu, X. Pan, and B. H. Wang, "A social force evacuation model with the leadership effect," Physica A: Statistical Mechanics and its Applications, vol. 400, pp. 93-99, 2014. https://doi.org/10.1016/j.physa.2013.12.049
  9. B. Anvari, M. G. Bell, A. Sivakumar, and W. Y. Ochieng, "Modelling shared space users via rule-based social force model," Transportation Research Part C: Emerging Technologies, vol. 51, pp. 83-103, 2015. https://doi.org/10.1016/j.trc.2014.10.012
  10. M. Li, Y. Zhao, L. He, W. Chen, and X. Xu, "The parameter calibration and optimization of social force model for the real-life 2013 Ya'an earthquake evacuation in China," Safety Science, vol. 79, pp. 243-253, 2015. https://doi.org/10.1016/j.ssci.2015.06.018
  11. W. Li, J. Gong, P. Yu, S. Shen, R. Li, and Q. Duan, "Simulation and analysis of congestion risk during escalator transfers using a modified social force model," Physica A: Statistical Mechanics and its Applications, vol. 420, pp. 28-40, 2015. https://doi.org/10.1016/j.physa.2014.10.044
  12. Q. G. Ji, R. Chi, and Z. M. Lu, "Anomaly detection and localisation in the crowd scenes using a block-based social force model," IET Image Processing, vol. 12, no. 1, pp. 133-137, 2018. https://doi.org/10.1049/iet-ipr.2016.0044
  13. J. Van Den Berg, S. J. Guy, M. Lin, and D. Manocha, "Reciprocal n-body collision avoidance," in Robotics Research. Heidelberg, Germany: Springer, 2011, pp. 3-19.
  14. P. Fiorini and Z. Shiller, "Motion planning in dynamic environments using velocity obstacles," The International Journal of Robotics Research, vol. 17, no. 7, pp. 760-772, 1998. https://doi.org/10.1177/027836499801700706
  15. T. Nagatani, "Jamming transition in the traffic-flow model with two-level crossings," Physical Review E, vol. 48, no. 5, pp. 3290-3294, 1993. https://doi.org/10.1103/PhysRevE.48.3290
  16. K. Takimoto and T. Nagatani, "Spatio-temporal distribution of escape time in evacuation process," Physica A: Statistical Mechanics and its Applications, vol. 320, pp. 611-621, 2003. https://doi.org/10.1016/S0378-4371(02)01540-6
  17. Y. Tajima and T. Nagatani, "Clogging transition of pedestrian flow in T-shaped channel," Physica A: Statistical Mechanics and its Applications, vol. 303, no. 1-2, pp. 239-250, 2002. https://doi.org/10.1016/S0378-4371(01)00424-1
  18. O. Khatib, "Real-time obstacle avoidance for manipulators and mobile robots," International Journal of Robotics Research, vol. 5, no. 1, pp. 90-98, 1986. https://doi.org/10.1177/027836498600500106
  19. O. Khatib, "The potential field approach and operational space formulation in robot control," in Proceedings of the 4th Yale Workshop on Applications of Adaptive System Theory, New Haven, CT, 1985, pp. 208-214.
  20. X. Zhang, X. Zhang, Y. Wang, and H. Yu, "Extended social force model-based mean shift for pedestrian tracking under obstacle avoidance," IET Computer Vision, vol. 11, no. 1, pp. 1-9, 2017. https://doi.org/10.1049/iet-cvi.2016.0022
  21. S. P. Hoogendoorn and P. H. Bovy, "Pedestrian route-choice and activity scheduling theory and models," Transportation Research Part B: Methodological, vol. 38, no. 2, pp. 169-190, 2004. https://doi.org/10.1016/S0191-2615(03)00007-9
  22. H. Yue, H. Guan, C. Shao, and X. Zhang, "Simulation of pedestrian evacuation with asymmetrical exits layout," Physica A: Statistical Mechanics and its Applications, vol. 390, no. 2, pp. 198-207, 2011. https://doi.org/10.1016/j.physa.2010.10.003
  23. A. Jo, T. Sano, Y. Ikehata, and Y. Ohmiya, "Analysis of crowd flow capacity through a door connected to a crowded corridor," Transportation Research Procedia, vol. 2, pp. 10-18, 2014. https://doi.org/10.1016/j.trpro.2014.09.003
  24. R. Y. Guo, H. J. Huang, and S. C. Wong, "Route choice in pedestrian evacuation under conditions of good and zero visibility: experimental and simulation results," Transportation Research Part B: Methodological, vol. 46, no. 6, pp. 669-686, 2012. https://doi.org/10.1016/j.trb.2012.01.002
  25. S. J. Kang, Y. Kim, and C. H. Kim, "Live path: adaptive agent navigation in the interactive virtual world," The Visual Computer, vol. 26, no. 6-8, pp. 467-476, 2010. https://doi.org/10.1007/s00371-010-0457-7
  26. A. Sud, E. Andersen, S. Curtis, M. C. Lin, and D. Manocha, "Real-time path planning in dynamic virtual environments using multiagent navigation graphs," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 3, pp. 526-538, 2008. https://doi.org/10.1109/TVCG.2008.27
  27. F. Haghpanah, J. Mitrani-Reiser, and B. W. Schafer, "Performance evaluation of pedestrian navigation algorithms for city evacuation modeling," in Proceedings of the 11th National Conference in Earthquake Engineering, Los Angeles, CA, 2018.