IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v450y2016icp416-434.html
   My bibliography  Save this article

Pedestrian movement analysis in transfer station corridor: Velocity-based and acceleration-based

Author

Listed:
  • Ji, Xiangfeng
  • Zhang, Jian
  • Hu, Yongkai
  • Ran, Bin

Abstract

In this paper, pedestrians are classified into aggressive and conservative ones by their temper. Aggressive pedestrians’ walking through crowd in transfer station corridor is analyzed. Treating pedestrians as particles, this paper uses the modified social force model (MSFM) as the building block, where forces involve self-driving force, repulsive force and friction force. The proposed model in this paper is a discrete model combining the MSFM and cellular automata (CA) model, where the updating rules of the CA are redefined with MSFM. Due to the continuity of values generated by the MSFM, we use the fuzzy logic to discretize the continuous values into cells pedestrians can move in one step. With the observation that stimulus around pedestrians influences their acceleration directly, an acceleration-based movement model is presented, compared to the generally reviewed velocity-based movement model. In the acceleration-based model, a discretized version of kinematic equation is presented based on the acceleration discretized with fuzzy logic. In real life, some pedestrians would rather keep their desired speed and this is also mimicked in this paper, which is called inertia. Compared to the simple triangular membership function, a trapezoidal membership function and a piecewise linear membership function are used to capture pedestrians’ inertia. With the trapezoidal and the piecewise linear membership function, many overlapping scenarios should be carefully handled and Dubois and Prade’s four-index method is used to completely describe the relative relationship of fuzzy quantities. Finally, a simulation is constructed to demonstrate the effect of our model.

Suggested Citation

  • Ji, Xiangfeng & Zhang, Jian & Hu, Yongkai & Ran, Bin, 2016. "Pedestrian movement analysis in transfer station corridor: Velocity-based and acceleration-based," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 416-434.
    • Handle: RePEc:eee:phsmap:v:450:y:2016:i:c:p:416-434
    DOI: 10.1016/j.physa.2015.12.139
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116000297
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2015.12.139?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hughes, Roger L., 2002. "A continuum theory for the flow of pedestrians," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 507-535, July.
    2. Zheng, Xiaoping & Cheng, Yuan, 2011. "Conflict game in evacuation process: A study combining Cellular Automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1042-1050.
    3. Hoogendoorn, Serge P. & van Wageningen-Kessels, Femke L.M. & Daamen, Winnie & Duives, Dorine C., 2014. "Continuum modelling of pedestrian flows: From microscopic principles to self-organised macroscopic phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 684-694.
    4. Dirk Helbing & Lubos Buzna & Anders Johansson & Torsten Werner, 2005. "Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions," Transportation Science, INFORMS, vol. 39(1), pages 1-24, February.
    5. Moonsoo Ko & Taewan Kim & Keemin Sohn, 2013. "Calibrating a social-force-based pedestrian walking model based on maximum likelihood estimation," Transportation, Springer, vol. 40(1), pages 91-107, January.
    6. Lachapelle, Aimé & Wolfram, Marie-Therese, 2011. "On a mean field game approach modeling congestion and aversion in pedestrian crowds," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1572-1589.
    7. 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.
    8. Tanimoto, Jun & Hagishima, Aya & Tanaka, Yasukaka, 2010. "Study of bottleneck effect at an emergency evacuation exit using cellular automata model, mean field approximation analysis, and game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5611-5618.
    9. Ji, Xiangfeng & Zhou, Xuemei & Ran, Bin, 2013. "A cell-based study on pedestrian acceleration and overtaking in a transfer station corridor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1828-1839.
    10. Ji, Xiangfeng & Zhang, Jian & Ran, Bin, 2013. "A study on pedestrian choice between stairway and escalator in the transfer station based on floor field cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5089-5100.
    11. repec:dau:papers:123456789/5946 is not listed on IDEAS
    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. Li, Yang & Chen, Maoyin & Zheng, Xiaoping & Dou, Zhan & Cheng, Yuan, 2020. "Relationship between behavior aggressiveness and pedestrian dynamics using behavior-based cellular automata model," Applied Mathematics and Computation, Elsevier, vol. 371(C).
    2. Chen, Jingxu & Li, Zhibin & Jiang, Hang & Zhu, Senlai & Wang, Wei, 2017. "Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 880-891.
    3. Cheng, Long & Cai, Xinmei & Liu, Zhuo & Huang, Zhiren & Chen, Wendong & Witlox, Frank, 2024. "Characterising travel behaviour patterns of transport hub station area users using mobile phone data," Journal of Transport Geography, Elsevier, vol. 116(C).
    4. Cao, Mengxiao & Zhang, Guijuan & Wang, Mengsi & Lu, Dianjie & Liu, Hong, 2017. "A method of emotion contagion for crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 250-258.
    5. Shang, Pan & Li, Ruimin & Guo, Jifu & Xian, Kai & Zhou, Xuesong, 2019. "Integrating Lagrangian and Eulerian observations for passenger flow state estimation in an urban rail transit network: A space-time-state hyper network-based assignment approach," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 135-167.
    6. Zhou, Xuemei & Hu, Jingjie & Ji, Xiangfeng & Xiao, Xiongziyan, 2019. "Cellular automaton simulation of pedestrian flow considering vision and multi-velocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 982-992.

    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. Zhou, Zi-Xuan & Nakanishi, Wataru & Asakura, Yasuo, 2021. "Data-driven framework for the adaptive exit selection problem in pedestrian flow: Visual information based heuristics approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    2. Saberi, Meead & Aghabayk, Kayvan & Sobhani, Amir, 2015. "Spatial fluctuations of pedestrian velocities in bidirectional streams: Exploring the effects of self-organization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 120-128.
    3. Qingyan Ning & Maosheng Li, 2022. "Modeling Pedestrian Detour Behavior By-Passing Conflict Areas," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    4. Duives, Dorine C. & Daamen, Winnie & Hoogendoorn, Serge P., 2016. "Continuum modelling of pedestrian flows — Part 2: Sensitivity analysis featuring crowd movement phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 36-48.
    5. Xu, Qiancheng & Chraibi, Mohcine & Tordeux, Antoine & Zhang, Jun, 2019. "Generalized collision-free velocity model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    6. 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).
    7. Zhang, Wenke & Zhang, Zhichao & Ma, Yueyao & Lee, Eric Wai Ming & Shi, Meng, 2024. "Psychological impatience in pedestrian evacuation: modelling, simulations and experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    8. Shi, Meng & Lee, Eric Wai Ming & Ma, Yi, 2018. "A novel grid-based mesoscopic model for evacuation dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 198-210.
    9. Ji, Xiangfeng & Zhou, Xuemei & Ran, Bin, 2013. "A cell-based study on pedestrian acceleration and overtaking in a transfer station corridor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1828-1839.
    10. 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.
    11. Liu, Yixue & Mao, Zhanli, 2022. "An experimental study on the critical state of herd behavior in decision-making of the crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    12. 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.
    13. Guo, Wei & Wang, Xiaolu & Liu, Mengting & Cheng, Yuan & Zheng, Xiaoping, 2015. "Modification of the dynamic floor field model by the heterogeneous bosons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 358-366.
    14. Miyagawa, Daiki & Ichinose, Genki, 2020. "Cellular automaton model with turning behavior in crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    15. Lachapelle, Aimé & Wolfram, Marie-Therese, 2011. "On a mean field game approach modeling congestion and aversion in pedestrian crowds," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1572-1589.
    16. Xie, Chuan-Zhi & Tang, Tie-Qiao & Hu, Peng-Cheng & Chen, Liang, 2022. "Observation and cellular-automaton based modeling of pedestrian behavior on an escalator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    17. Li, Jun & Fu, Siyao & He, Haibo & Jia, Hongfei & Li, Yanzhong & Guo, Yi, 2015. "Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 304-321.
    18. 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.
    19. 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.
    20. 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.

    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:eee:phsmap:v:450:y:2016:i:c:p:416-434. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.