IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v10y2016i7p1.html
   My bibliography  Save this article

Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/58254/31134
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/mas/article/view/58254
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2019. "When ‘push’ does not come to ‘shove’: Revisiting ‘faster is slower’ in collective egress of human crowds," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 51-69.
    2. Ziyou Gao & Yunchao Qu & Xingang Li & Jiancheng Long & Hai-Jun Huang, 2014. "Simulating the Dynamic Escape Process in Large Public Places," Operations Research, INFORMS, vol. 62(6), pages 1344-1357, December.
    3. 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.
    4. Zhou, Zi-Xuan & Nakanishi, Wataru & Asakura, Yasuo, 2021. "Route choice in the pedestrian evacuation: Microscopic formulation based on visual information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    5. Li, Maosheng & Shu, Panpan & Xiao, Yao & Wang, Pu, 2021. "Modeling detour decision combined the tactical and operational layer based on perceived density," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    6. Heng Wang & Zehao Jiang & Tiandong Xu & Feng Li, 2021. "A Quantitative Approach of Subway Station Passengers’ Heterogeneity of Decision Preference Considering Personality Traits during Emergency Evacuation," Sustainability, MDPI, vol. 13(22), pages 1-14, November.
    7. Ken Hidaka & Toshiyuki Yamamoto, 2021. "Activity Scheduling Behavior of the Visitors to an Outdoor Recreational Facility Using GPS Data," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
    8. Tang, Ming & Jia, Hongfei & Ran, Bin & Li, Jun, 2016. "Analysis of the pedestrian arching at bottleneck based on a bypassing behavior model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 242-258.
    9. Xianing Wang & Zhan Zhang & Ying Wang & Jun Yang & Linjun Lu, 2022. "A Study on Safety Evaluation of Pedestrian Flows Based on Partial Impact Dynamics by Real-Time Data in Subway Stations," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    10. Dirk Helbing & Pratik Mukerji, "undated". "Crowd Disasters as Systemic Failures: Analysis of the Love Parade Disaster," Working Papers ETH-RC-12-010, ETH Zurich, Chair of Systems Design.
    11. Li, Lin & Yu, Zhonghai & Chen, Yang, 2014. "Evacuation dynamic and exit optimization of a supermarket based on particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 157-172.
    12. Zhang, Yihao & Chai, Zhaojie & Lykotrafitis, George, 2021. "Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    13. Xiao, Yao & Yang, Mofeng & Zhu, Zheng & Yang, Hai & Zhang, Lei & Ghader, Sepehr, 2021. "Modeling indoor-level non-pharmaceutical interventions during the COVID-19 pandemic: A pedestrian dynamics-based microscopic simulation approach," Transport Policy, Elsevier, vol. 109(C), pages 12-23.
    14. Milad Haghani & Majid Sarvi & Zahra Shahhoseini & Maik Boltes, 2016. "How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-24, November.
    15. Abdelghany, Ahmed & Abdelghany, Khaled & Mahmassani, Hani, 2016. "A hybrid simulation-assignment modeling framework for crowd dynamics in large-scale pedestrian facilities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 159-176.
    16. Qingyan Ning & Maosheng Li, 2022. "Modeling Pedestrian Detour Behavior By-Passing Conflict Areas," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    17. Wang, Shuaian & Zhang, Wei & Qu, Xiaobo, 2018. "Trial-and-error train fare design scheme for addressing boarding/alighting congestion at CBD stations," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 318-335.
    18. 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.
    19. Ma, Wanjing & Li, Li & Wang, Yinhai, 2016. "A driving force model for non-strict priority crossing behaviors of right-turn driversAuthor-Name: Lin, Dianchao," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 230-244.
    20. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.

    More about this item

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:masjnl:v:10:y:2016:i:7:p:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.