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A micro-simulation model for pedestrian flows

Author

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  • Gipps, P.G.
  • Marksjö, B.

Abstract

The ability to predict how changes in the walking environment will affect the pedestrian flow is important to the designers of buildings and other constructed facilities. These changes can act on an individual pedestrian directly by diverting him from his preferred route, and indirectly through their effect on the other pedestrians. If the behaviour of individuals can be adequately modelled, and the appropriate distribution of pedestrian types is employed, their corporate behaviour be realistic. This paper presents a model for the interactions between pedestrians which is intended for use in a graphical computer simulation. The program runs on a microcomputer and uses interactive colour graphics to display the operation of the model and assist in the validation and verification of the model.

Suggested Citation

  • Gipps, P.G. & Marksjö, B., 1985. "A micro-simulation model for pedestrian flows," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 27(2), pages 95-105.
  • Handle: RePEc:eee:matcom:v:27:y:1985:i:2:p:95-105
    DOI: 10.1016/0378-4754(85)90027-8
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    Cited by:

    1. Wei Wang & Yindong Ji & Zhonghao Zhao & Haodong Yin, 2024. "Simulation Optimization of Station-Level Control of Large-Scale Passenger Flow Based on Queueing Network and Surrogate Model," Sustainability, MDPI, vol. 16(17), pages 1-35, August.
    2. Zhang, Qi & Han, Baoming, 2011. "Simulation model of pedestrian interactive behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 636-646.
    3. Bin Lei & Jinliang Xu & Menghui Li & Haoru Li & Jin Li & Zhen Cao & Yarui Hao & Yuan Zhang, 2019. "Enhancing Role of Guiding Signs Setting in Metro Stations with Incorporation of Microscopic Behavior of Pedestrians," Sustainability, MDPI, vol. 11(21), pages 1-14, November.
    4. Ezaki, Takahiro & Yanagisawa, Daichi & Ohtsuka, Kazumichi & Nishinari, Katsuhiro, 2012. "Simulation of space acquisition process of pedestrians using Proxemic Floor Field Model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 291-299.
    5. 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).
    6. Srećko KRILE & Nikolai MAIOROV & Vladimir FETISOV, 2018. "Forecasting The Operational Activities Of The Sea Passenger Terminal Using Intelligent Technologies," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 13(1), pages 27-36, March.
    7. Perez, Gay Jane & Tapang, Giovanni & Lim, May & Saloma, Caesar, 2002. "Streaming, disruptive interference and power-law behavior in the exit dynamics of confined pedestrians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 609-618.
    8. Blue, Victor J. & Adler, Jeffrey L., 2001. "Cellular automata microsimulation for modeling bi-directional pedestrian walkways," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 293-312, March.
    9. 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.
    10. Goldsztein, Guillermo H., 2017. "Crowd of individuals walking in opposite directions. A toy model to study the segregation of the group into lanes of individuals moving in the same direction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 162-173.
    11. 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.

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