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An Investigation Capability Model for Bidirectional Pedestrian Flow

Author

Listed:
  • Mohammed Shuaib
  • Zarita Zainuddin

Abstract

The pedestrian traffic flow in bidirectional walkways is very crucial aspect influenced by the level of pedestrians’ decisions. In this article, the authors show that the simulated pedestrians walking based on crowd dynamics models of low level mechanism of navigation (operational level) are short-sighted in avoiding counter flow. Such limitation resulted in unrealistic formation of motion in bidirectional flow, that the movement is less systematic and the lanes are less coherent than what in real situation. To obtain a more representative model, the authors improve the investigation capability model as a tactical decision model to be incorporated into a crowd dynamics model to reproduce better formation of motion. This is accomplished by granting the pedestrians the ability to investigate the macroscopic behaviors in their investigation areas and make decisions for convenience flow. The new model considers the average density and flow inside such areas and models their effect on the pedestrians' decisions. Simulations are performed to validate the work qualitatively by tracing the behavior of the simulated pedestrians and studying the impact of this behavior on the self-organized phenomenon- lane formation. Furthermore, the fundamental diagram of bidirectional flow is reproduced and compared with experimental fundamental diagrams.

Suggested Citation

  • Mohammed Shuaib & Zarita Zainuddin, 2015. "An Investigation Capability Model for Bidirectional Pedestrian Flow," Modern Applied Science, Canadian Center of Science and Education, vol. 9(12), pages 1-88, November.
  • Handle: RePEc:ibn:masjnl:v:9:y:2015:i:12:p:88
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    References listed on IDEAS

    as
    1. Anders Johansson & Dirk Helbing & Pradyumn K. Shukla, 2007. "Specification Of The Social Force Pedestrian Model By Evolutionary Adjustment To Video Tracking Data," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(supp0), pages 271-288.
    2. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    3. Osama Moh'd Alia & Mohammed Mahmod Shuaib, 2014. "A Harmony Search Algorithm for the Reproduction of Experimental Data in the Social Force Model," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, April.
    4. 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.
    5. 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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    Cited by:

    1. Mohammed Mahmod Shuaib, 2016. "Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior," Modern Applied Science, Canadian Center of Science and Education, vol. 10(7), pages 1-1, July.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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