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Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior

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  • Mohammed Mahmod Shuaib

Abstract

Incorporating decision-making capability as an intelligence aspect into crowd dynamics models is crucial factor for reproducing realistic pedestrian flow. Crowd dynamics models are still suffering from poor representation of essential behaviors such as lane changing behavior. In this article, we provide the simulated pedestrians in the social force model more intelligence as an extension to the pedestrian’s investigation capability in bidirectional walkways, to let the model appear more representative of what actually happens in reality. In the proposed model, the lane’s structure is modeled as social network. Thereby, the simulated pedestrians with inconvenient walking can detect the available lanes inside his environment, investigate their attractions, and then make decisions to join the most attractive one. Simulations are performed to validate the work qualitatively by tracing the behavior of the simulated pedestrians and studying the impact of this behavior on lane formation. Finally, a quantitative measurement is used to study the effect of our contribution on the pedestrians’ efficiency of motion.

Suggested Citation

  • 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.
    • Handle: RePEc:ibn:masjnl:v:10:y:2016:i:7:p:1
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    References listed on IDEAS

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    1. 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.
    2. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    3. 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.
    4. Guo, Ren-Yong, 2014. "Simulation of spatial and temporal separation of pedestrian counter flow through a bottleneck," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 428-439.
    5. 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.
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    Cited by:

    1. Banerjee, Arunabha & Das, Sanhita & Maurya, Akhilesh Kumar, 2024. "Behavioural characteristics influencing walking speed of pedestrians over elevated facilities: A case study of India," Transport Policy, Elsevier, vol. 147(C), pages 169-182.

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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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