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Modeling and simulation of pedestrian traffic flow

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  • Løvås, Gunnar G.

Abstract

Questions about the efficiency and safety of pedestrian traffic systems are of major importance in the planning and design of such systems. As the use of functional--or performance-based--requirements becomes more popular, there is also an increasing need for methods and tools which can be used to evaluate if these functional requirements are met. This article presents a stochastic model based on the following assumptions: Any pedestrian facility can be modeled as a network of walkway sections. Pedestrian flow in this network can be modeled as a queueing network process, where each pedestrian is treated as a separate flow object, interacting with the other objects. Such a microscopic model is useful because it makes detailed modeling of human behavior possible. This article also presents a simulation tool, of which the main objective is to estimate the relevant performance measures of the pedestrian traffic system. The article includes two examples.

Suggested Citation

  • Løvås, Gunnar G., 1994. "Modeling and simulation of pedestrian traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 28(6), pages 429-443, December.
    • Handle: RePEc:eee:transb:v:28:y:1994:i:6:p:429-443
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    Citations

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    Cited by:

    1. Flötteröd, Gunnar & Lämmel, Gregor, 2015. "Bidirectional pedestrian fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 194-212.
    2. Hänseler, Flurin S. & Lam, William H.K. & Bierlaire, Michel & Lederrey, Gael & Nikolić, Marija, 2017. "A dynamic network loading model for anisotropic and congested pedestrian flows," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 149-168.
    3. Hänseler, Flurin S. & Bierlaire, Michel & Scarinci, Riccardo, 2016. "Assessing the usage and level-of-service of pedestrian facilities in train stations: A Swiss case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 106-123.
    4. 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.
    5. Hu, Lu & Zhao, Bin & Zhu, Juanxiu & Jiang, Yangsheng, 2019. "Two time-varying and state-dependent fluid queuing models for traffic circulation systems," European Journal of Operational Research, Elsevier, vol. 275(3), pages 997-1019.
    6. Lovas, Gunnar G., 1995. "On performance measures for evacuation systems," European Journal of Operational Research, Elsevier, vol. 85(2), pages 352-367, September.
    7. Hänseler, Flurin S. & van den Heuvel, Jeroen P.A. & Cats, Oded & Daamen, Winnie & Hoogendoorn, Serge P., 2020. "A passenger-pedestrian model to assess platform and train usage from automated data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 948-968.
    8. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
    9. Huang, Keke & Zheng, Xiaoping & Cheng, Yuan & Yang, Yeqing, 2017. "Behavior-based cellular automaton model for pedestrian dynamics," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 417-424.
    10. Gao, Jin & He, Jun & Gong, Jinghai, 2020. "A simplified method to provide evacuation guidance in a multi-exit building under emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    11. Kim, Inhi & Galiza, Ronald & Ferreira, Luis, 2013. "Modeling pedestrian queuing using micro-simulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 232-240.
    12. Piotr Gołębiowski & Jolanta Żak & Ilona Jacyna-Gołda, 2020. "Approach to the Proecological Distribution of the Traffic Flow on the Transport Network from the Point of View of Carbon Dioxide," Sustainability, MDPI, vol. 12(17), pages 1-16, August.
    13. Chen, Yanru & Yi, Bing & Jiang, Yangsheng & Sun, Jidong & Wahab, M.I.M., 2018. "Inter-arrival time distribution of passengers at service facilities in underground subway stations: A case study of the metropolitan city of Chengdu in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 227-251.
    14. Hoogendoorn, S. P. & Bovy, P. H. L., 2004. "Pedestrian route-choice and activity scheduling theory and models," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 169-190, February.
    15. Zhao, Daoliang & Yang, Lizhong & Li, Jian, 2008. "Occupants’ behavior of going with the crowd based on cellular automata occupant evacuation model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3708-3718.
    16. 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.

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