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Modelling and simulating the leader–follower behaviour of pedestrians in unidirectional flow

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  • Sobhana, Karthika P.
  • Choubey, Nipun
  • Verma, Ashish

Abstract

The following (or) queuing behaviour of pedestrians, wherein people walk one after the other in a line is a common occurrence in pedestrian facilities or crowd gatherings. Though many studies have explored this behaviour, especially using single-file experiments, this behaviour cannot be treated in isolation from other walking behaviours like overtaking or lane-changing. Also, the contemporary models assume that the person ahead is the leader by all the pedestrians. In the real-world, however, the follower may not consider their predecessor as a leader and modulate their movements according to the leader dynamics. Yet, most pedestrian models are deterministic and do not incorporate uncertainty and fluctuations of perception and behaviour. The proposed following model is nondeterministic and data-driven We propose a methodology to model the pedestrian walking dynamics in a unidirectional single channel flow by jointly modelling the aspect of probabilistic consideration of leader, lane changing, and following behaviour. The proposed behavioural model is calibrated using field data of pilgrim’s movement in a narrow corridor in Kumbh Mela, a mass religious gathering in India. It is noted that the probability of lane change is directly proportional to the adjacent lane spacing and inversely proportional to the current lane spacing. The threshold spacing, within which the chances of the following pedestrian to consider the pedestrian ahead as a leader is obtained to be 1.2 m for the final model. An agent-based model is developed based on the calibrated behavioural model and several scenarios such as speed variations, gender influences, and flow variations are tested. It was observed that when few pedestrians stop in between for a while, the average speeds reduced from 1 m/s to 0.57 m/s and the probability of following pedestrians doing lane change increased. Also, the variation in spacing is observed to have more spread when the agents move slowly. The proposed agent-based microsimulation model can be used by the event managers by allowing them to test various possible scenarios during the event-preparation phase of crowd management.

Suggested Citation

  • Sobhana, Karthika P. & Choubey, Nipun & Verma, Ashish, 2023. "Modelling and simulating the leader–follower behaviour of pedestrians in unidirectional flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    • Handle: RePEc:eee:phsmap:v:623:y:2023:i:c:s0378437123003795
    DOI: 10.1016/j.physa.2023.128824
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    References listed on IDEAS

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    1. Robin, Th. & Antonini, G. & Bierlaire, M. & Cruz, J., 2009. "Specification, estimation and validation of a pedestrian walking behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 36-56, January.
    2. von Krüchten, Cornelia & Schadschneider, Andreas, 2017. "Empirical study on social groups in pedestrian evacuation dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 129-141.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    4. 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.
    5. 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.
    6. Antonini, Gianluca & Bierlaire, Michel & Weber, Mats, 2006. "Discrete choice models of pedestrian walking behavior," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 667-687, September.
    7. 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.
    8. Zhilu Yuan & Hongfei Jia & Linfeng Zhang & Lei Bian, 2017. "Simulation of Pedestrian Behavior in the Collision-Avoidance Process considering Their Moving Preferences," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-11, May.
    9. Jun Hu & Zhongwen Li & Hong Zhang & Juan Wei & Lei You & Peng Chen, 2015. "Experiment and simulation of the bidirectional pedestrian flow model with overtaking and herding behavior," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(11), pages 1-14.
    10. Burstedde, C & Klauck, K & Schadschneider, A & Zittartz, J, 2001. "Simulation of pedestrian dynamics using a two-dimensional cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 507-525.
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