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Social force models for pedestrian traffic – state of the art

Author

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  • Xu Chen
  • Martin Treiber
  • Venkatesan Kanagaraj
  • Haiying Li

Abstract

Pedestrian simulation plays an important role in the fields of transport station management, building evacuation and safety management of large public events. Among the continuous pedestrian flow models, the social force model is one of the most widespread and supports all of the above use cases. Since its initial proposal by Helbing and Molnar [(1995). Social force model for pedestrian dynamics. Physical Review E, 51, 4282], many improvements of the social force model have been put forward for solving various, but mostly specific, problems. However, an up-to-date and essentially comprehensive review bringing all the model variants into a common context is missing. In this paper, we propose such a framework in terms of assessment criteria for pedestrian models considering pedestrian attributes, motion base cases, self-organisation phenomena and some special cases. Starting with the initial version of Helbing and Molnar [(1995). Social force model for pedestrian dynamics. Physical Review E, 51, 4282] and the escape panic version of Helbing, Farkas, and Vicsek [(2000a). Simulating dynamical features of escape panic. Nature, 407, 487–490], we classify the improvements and assess their degree of the improvements. Further discussion is presented from the perspectives of description ability, parameter calibration and flexible application in a complex environment.

Suggested Citation

  • Xu Chen & Martin Treiber & Venkatesan Kanagaraj & Haiying Li, 2018. "Social force models for pedestrian traffic – state of the art," Transport Reviews, Taylor & Francis Journals, vol. 38(5), pages 625-653, September.
    • Handle: RePEc:taf:transr:v:38:y:2018:i:5:p:625-653
    DOI: 10.1080/01441647.2017.1396265
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    Cited by:

    1. Zhang, Hui & Xu, Jie & Jia, Limin & Shi, Yihan, 2022. "Modelling the walking behavior of pedestrians in the junction with chamfer zone of subway station," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
    2. Liu, Qiujia & Lu, Linjun & Zhang, Yijing & Hu, Miaoqing, 2022. "Modeling the dynamics of pedestrian evacuation in a complex environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    3. Ma, Liang & Chen, Bin & Wang, Xiaodong & Zhu, Zhengqiu & Wang, Rongxiao & Qiu, Xiaogang, 2019. "The analysis on the desired speed in social force model using a data driven approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 894-911.
    4. Constanza Flores & Han Soo Lee & Erick Mas, 2024. "Understanding Tsunami Evacuation via a Social Force Model While Considering Stress Levels Using Agent-Based Modelling," Sustainability, MDPI, vol. 16(10), pages 1-20, May.
    5. Lu, Peng & Wen, Feier & Li, Yan & Chen, Dianhan, 2021. "Multi-agent modeling of crowd dynamics under mass shooting cases," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    6. Hu, Xiangmin & Chen, Tao & Deng, Kaifeng & Wang, Guanning, 2023. "Effects of aggressiveness on pedestrian room evacuation using extended cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    7. Sticco, I.M. & Frank, G.A. & Dorso, C.O., 2021. "Social Force Model parameter testing and optimization using a high stress real-life situation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    8. Cheng, Han & Peng, Fei & Huang, Danyan & Liu, Shaobo & Ni, Yong & Yang, Lizhong, 2020. "Experimental study on dynamics characteristic parameter of turning behavior in self-driven mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    9. Haghani, Milad, 2021. "The knowledge domain of crowd dynamics: Anatomy of the field, pioneering studies, temporal trends, influential entities and outside-domain impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    10. Rangel-Galván, Maricruz & Ballinas-Hernández, Ana L. & Rangel-Galván, Violeta, 2024. "Thermo-inspired model of self-propelled hard disk agents for heterogeneous bidirectional pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    11. Li, Zexu & Fang, Lei, 2024. "On the ideal gas law for crowds with high pressure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    12. Cristiani, E. & Menci, M. & Malagnino, A. & Amaro, G.G., 2023. "An all-densities pedestrian simulator based on a dynamic evaluation of the interpersonal distances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
    13. Ding, Ning & Zhu, Yu & Liu, Xinyan & Dong, Dapeng & Wang, Yang, 2024. "A modified social force model for crowd evacuation considering collision predicting behaviors," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    14. Tian, Jiangtao & Li, Xingli & Guo, Qinghua & Kuang, Hua, 2024. "Dynamics characteristic of pedestrians’ particular overtaking behavior based on an improved social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).

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