IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v643y2024ics0378437124002978.html
   My bibliography  Save this article

A modified social force model for pedestrian-bicycle mixed flows and its application on evaluating the conflict risk in shared roads

Author

Listed:
  • Wang, Weili
  • Zhou, Hui
  • Lo, Jacqueline T.Y.
  • Lo, S.M.
  • Wang, Yiwen

Abstract

As sustainable modes of transport, walking and cycling are the major choices for short trips. The mixed flow of pedestrians and bicycles is often observed on the roads, but its dynamics and conflict risks have not been well investigated. As commonly observed, pedestrians walk along the road boundaries in the pedestrian-bicycle shared roads. When two or more bicycles share the road, the rear bicycle may choose to either follow or overtake the preceding bicycle under specific criteria. To better reproduce this phenomenon, this study proposed a modified social model. Specifically, self-driving force, force from boundaries, force from other pedestrians and force from bicycles were considered in simulating pedestrian movement. Additionally, the modeling of bicycle movement explicitly takes into account the behavior force for following or overtaking the preceding bicycle. YOLO v5 object detection and DeepSORT multi-object tracking algorithms were applied to extract pedestrian and bicycle trajectories captured by the camera on an unmanned aerial vehicle (UAV). Then the model was calibrated using a genetic algorithm to minimize the discrepancy between the simulated and observed trajectories. Under both unidirectional and bidirectional flow scenarios, the proposed model demonstrates good accuracy in reproducing individual movements and lane-formation phenomena for bidirectional pedestrian-bicycle mixed flows. Furthermore, the calibrated model was applied to evaluate the conflict risk of pedestrians and bicycles in a straight road and an intersection on campus. The safety assessment results indicate that lower density and fewer bicycles in the mixed flow can effectively reduce the risk of conflicts. This study can help understand interactions of pedestrians and cyclists in mixed flow conditions and provide theoretical support for the planning and safety evaluation of pedestrian-bicycle shared roads.

Suggested Citation

  • Wang, Weili & Zhou, Hui & Lo, Jacqueline T.Y. & Lo, S.M. & Wang, Yiwen, 2024. "A modified social force model for pedestrian-bicycle mixed flows and its application on evaluating the conflict risk in shared roads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    • Handle: RePEc:eee:phsmap:v:643:y:2024:i:c:s0378437124002978
    DOI: 10.1016/j.physa.2024.129788
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124002978
    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.2024.129788?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. Seyfried, Armin & Steffen, Bernhard & Lippert, Thomas, 2006. "Basics of modelling the pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(1), pages 232-238.
    2. Guo, Ning & Jiang, Rui & Wong, S.C. & Hao, Qing-Yi & Xue, Shu-Qi & Xiao, Yao & Wu, Chao-Yun, 2020. "Modeling the interactions of pedestrians and cyclists in mixed flow conditions in uni- and bidirectional flows on a shared pedestrian-cycle road," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 259-284.
    3. Tie-Qiao Tang & Hai-Jun Huang & Hua-Yan Shang, 2010. "A Dynamic Model For The Heterogeneous Traffic Flow Consisting Of Car, Bicycle And Pedestrian," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 159-176.
    4. Luo, Lin & Luo, Yangqi & Feng, Yujing & Li, Tao & Fu, Zhijian, 2022. "Experimental investigation on pedestrian–bicycle mixed merging flow in T-junction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    5. Wang, Weili & Zhang, Jingjing & Li, Haicheng & Xie, Qimiao, 2020. "Experimental study on unidirectional pedestrian flows in a corridor with a fixed obstacle and a temporary obstacle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    6. Xia, Yingji & Sun, Zhe & Qu, Zhaowei & Liu, Tianze & Li, Zhihui & Gao, Yuhong, 2021. "Reaction model of conflictive e-bikes and numerical simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    7. Hou, Xianlei & Zhang, Rui & Yang, Minghui & Cheng, Shida, 2024. "Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    Full references (including those not matched with items on IDEAS)

    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. Yue, Hao & Zhang, Junyao & Chen, Wenxin & Wu, Xinsen & Zhang, Xu & Shao, Chunfu, 2021. "Simulation of the influence of spatial obstacles on evacuation pedestrian flow in walking facilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    2. Chen, Juan & Luo, Qian & Wang, Qiao & Lo, Jacqueline T.Y. & Ma, Jian, 2024. "Experimental study on individual and crowd movement features around obstacles with different shape and size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    3. Xiaomeng Wang & Ling Peng & Tianhe Chi & Mengzhu Li & Xiaojing Yao & Jing Shao, 2015. "A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-20, December.
    4. Xiaobin Yang & Zhilong Chen & Hao Cai & Linjian Ma, 2014. "A Framework for Assessment of the Influence of China’s Urban Underground Space Developments on the Urban Microclimate," Sustainability, MDPI, vol. 6(12), pages 1-31, November.
    5. 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.
    6. Cui, Geng & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2023. "Learning from experimental data to simulate pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    7. Cirillo, E.N.M. & Colangeli, M. & Muntean, A., 2017. "Trapping in bottlenecks: Interplay between microscopic dynamics and large scale effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 30-38.
    8. Sun, Yi, 2018. "Kinetic Monte Carlo simulations of two-dimensional pedestrian flow models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 836-847.
    9. Johansson, Fredrik & Peterson, Anders & Tapani, Andreas, 2015. "Waiting pedestrians in the social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 95-107.
    10. Chen, Chang-Kun & Li, Jian & Zhang, Dong, 2012. "Study on evacuation behaviors at a T-shaped intersection by a force-driving cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2408-2420.
    11. Fu, Zhijian & Zhou, Xiaodong & Zhu, Kongjin & Chen, Yanqiu & Zhuang, Yifan & Hu, Yuqi & Yang, Lizhong & Chen, Changkun & Li, Jian, 2015. "A floor field cellular automaton for crowd evacuation considering different walking abilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 294-303.
    12. Feliciani, Claudio & Nishinari, Katsuhiro, 2016. "An improved Cellular Automata model to simulate the behavior of high density crowd and validation by experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 135-148.
    13. Li, Wenhang & Gong, Jianhua & Yu, Ping & Shen, Shen & Li, Rong & Duan, Qishen, 2015. "Simulation and analysis of congestion risk during escalator transfers using a modified social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 28-40.
    14. Ha, Vi & Lykotrafitis, George, 2012. "Agent-based modeling of a multi-room multi-floor building emergency evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2740-2751.
    15. Ana Luisa Ballinas-Hernández & Angélica Muñoz-Meléndez & Alejandro Rangel-Huerta, 2011. "Multiagent System Applied to the Modeling and Simulation of Pedestrian Traffic in Counterflow," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(3), pages 1-2.
    16. Simone Göttlich & Sebastian Kühn & Jan Peter Ohst & Stefan Ruzika, 2016. "Evacuation modeling: a case study on linear and nonlinear network flow models," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 219-239, September.
    17. Wang, Yan & Peng, Zhongyi & Chen, Qun, 2018. "Simulated interactions of pedestrian crossings and motorized vehicles in residential areas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1046-1060.
    18. Bosina, Ernst & Weidmann, Ulrich, 2017. "Estimating pedestrian speed using aggregated literature data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 1-29.
    19. Cheng, Zhiyang & Yue, Hao & Zhang, Ning & Zhang, Xu, 2024. "Research on mechanism and simulation for avoiding behavior of individual pedestrian," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    20. Ding, Ning & Zhu, Yu & Liu, Xinyan & Dong, Dapeng & Wang, Yang, 2024. "A modified social force model for crowd evacuation considering collision predicting behaviors," Applied Mathematics and Computation, Elsevier, vol. 466(C).

    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:643:y:2024:i:c:s0378437124002978. 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.