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Basics of modelling the pedestrian flow

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  • Seyfried, Armin
  • Steffen, Bernhard
  • Lippert, Thomas

Abstract

For the modelling of pedestrian dynamics we treat persons as self-driven objects moving in a continuous space. On the basis of a modified social force model we qualitatively analyze the influence of various approaches for the interaction between the pedestrians on the resulting velocity–density relation. To focus on the role of the required space and remote force we choose a one-dimensional model for this investigation. For those densities, where in two dimensions also passing is no longer possible and the mean value of the velocity depends primarily on the interaction, we obtain the following result: If the model increases the required space of a person with increasing current velocity, the reproduction of the typical form of the fundamental diagram is possible. Furthermore, we demonstrate the influence of the remote force on the velocity–density relation.

Suggested Citation

  • Seyfried, Armin & Steffen, Bernhard & Lippert, Thomas, 2006. "Basics of modelling the pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(1), pages 232-238.
    • Handle: RePEc:eee:phsmap:v:368:y:2006:i:1:p:232-238
    DOI: 10.1016/j.physa.2005.11.052
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    Citations

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    Cited by:

    1. Cirillo, E.N.M. & Colangeli, M. & Muntean, A., 2017. "Trapping in bottlenecks: Interplay between microscopic dynamics and large scale effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 30-38.
    2. Yamamoto, Hiroki & Yanagisawa, Daichi & Feliciani, Claudio & Nishinari, Katsuhiro, 2019. "Body-rotation behavior of pedestrians for collision avoidance in passing and cross flow," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 486-510.
    3. Cao, Shuchao & Song, Weiguo & Lv, Wei & Fang, Zhiming, 2015. "A multi-grid model for pedestrian evacuation in a room without visibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 45-61.
    4. Li, Wenhang & Gong, Jianhua & Yu, Ping & Shen, Shen & Li, Rong & Duan, Qishen, 2015. "Simulation and analysis of congestion risk during escalator transfers using a modified social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 28-40.
    5. Chraibi, Mohcine & Ensslen, Tim & Gottschalk, Hanno & Saadi, Mohamed & Seyfried, Armin, 2016. "Assessment of models for pedestrian dynamics with functional principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 475-489.
    6. Simone Göttlich & Sebastian Kühn & Jan Peter Ohst & Stefan Ruzika, 2016. "Evacuation modeling: a case study on linear and nonlinear network flow models," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 219-239, September.
    7. Sun, Yi, 2018. "Kinetic Monte Carlo simulations of two-dimensional pedestrian flow models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 836-847.
    8. Johansson, Fredrik & Peterson, Anders & Tapani, Andreas, 2015. "Waiting pedestrians in the social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 95-107.
    9. Ana Luisa Ballinas-Hernández & Angélica Muñoz-Meléndez & Alejandro Rangel-Huerta, 2011. "Multiagent System Applied to the Modeling and Simulation of Pedestrian Traffic in Counterflow," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(3), pages 1-2.
    10. Chen, Chang-Kun & Li, Jian & Zhang, Dong, 2012. "Study on evacuation behaviors at a T-shaped intersection by a force-driving cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2408-2420.
    11. Izquierdo, J. & Montalvo, I. & Pérez, R. & Fuertes, V.S., 2009. "Forecasting pedestrian evacuation times by using swarm intelligence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1213-1220.
    12. Bosina, Ernst & Weidmann, Ulrich, 2017. "Estimating pedestrian speed using aggregated literature data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 1-29.
    13. Abdelghany, Ahmed & Abdelghany, Khaled & Mahmassani, Hani, 2016. "A hybrid simulation-assignment modeling framework for crowd dynamics in large-scale pedestrian facilities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 159-176.
    14. Tipakornkiat, Chalat & Limanond, Thirayoot & Kim, Hyunmyung, 2012. "Determining an influencing area affecting walking speed on footpath: A case study of a footpath in CBD Bangkok, Thailand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5453-5464.
    15. Fu, Zhijian & Zhou, Xiaodong & Zhu, Kongjin & Chen, Yanqiu & Zhuang, Yifan & Hu, Yuqi & Yang, Lizhong & Chen, Changkun & Li, Jian, 2015. "A floor field cellular automaton for crowd evacuation considering different walking abilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 294-303.
    16. Feliciani, Claudio & Nishinari, Katsuhiro, 2016. "An improved Cellular Automata model to simulate the behavior of high density crowd and validation by experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 135-148.
    17. Ha, Vi & Lykotrafitis, George, 2012. "Agent-based modeling of a multi-room multi-floor building emergency evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2740-2751.
    18. Seitz, Michael J. & Dietrich, Felix & Köster, Gerta, 2015. "The effect of stepping on pedestrian trajectories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 594-604.
    19. Pereira, L.A. & Burgarelli, D. & Duczmal, L.H. & Cruz, F.R.B., 2017. "Emergency evacuation models based on cellular automata with route changes and group fields," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 97-110.
    20. Fu, Zhijian & Luo, Lin & Yang, Yue & Zhuang, Yifan & Zhang, Peitong & Yang, Lizhong & Yang, Hongtai & Ma, Jian & Zhu, Kongjin & Li, Yanlai, 2016. "Effect of speed matching on fundamental diagram of pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 31-42.
    21. Fang, Jun & Qin, Zheng & Hu, Hao & Xu, Zhaohui & Li, Huan, 2012. "The fundamental diagram of pedestrian model with slow reaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6112-6120.
    22. Parisi, Daniel R. & Gilman, Marcelo & Moldovan, Herman, 2009. "A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3600-3608.
    23. Fu, Zhijian & Yang, Lizhong & Chen, Yanqiu & Zhu, Kongjin & Zhu, Shi, 2013. "The effect of individual tendency on crowd evacuation efficiency under inhomogeneous exit attraction using a static field modified FFCA model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6090-6099.
    24. Cui, Geng & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2023. "Learning from experimental data to simulate pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).

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    Keywords

    Pedestrian dynamics;

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