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Bicycle longitudinal elastic cellular automaton model based on behavior characteristics analysis

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  • Yang, Xiaofang
  • Fu, Qiang

Abstract

In response to the insufficient consideration of cyclists' behavioral analysis in previous studies, it is proposed that the spatial occupancy of cyclists is not a traditional rectangle but more like a horizontally oriented box plot. The narrower front and rear spatial occupancy allow cyclists to laterally offset slightly while following more closely longitudinally. By discretizing the cellular space and allowing cell overlaps, an improved one-dimensional cellular automaton model is introduced. An elasticity coefficient is introduced to characterize the probability of cyclists choosing to follow closely based on density variations. Comparisons with representative experimental data and existing models demonstrate that the proposed model exhibits higher congestion density and maintains high flow rates even at high densities, aligning more closely with real-world scenarios.

Suggested Citation

  • Yang, Xiaofang & Fu, Qiang, 2025. "Bicycle longitudinal elastic cellular automaton model based on behavior characteristics analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 667(C).
    • Handle: RePEc:eee:phsmap:v:667:y:2025:i:c:s037843712500202x
    DOI: 10.1016/j.physa.2025.130550
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    References listed on IDEAS

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    1. Gould, Gregory & Karner, Alex, 2009. "Modeling Bicycle Facility Operation: a Cellular Automaton Approach," Institute of Transportation Studies, Working Paper Series qt1xn1j5vh, Institute of Transportation Studies, UC Davis.
    2. Xiaonian Shan & Zhibin Li & Xiaohong Chen & Jianhong Ye, 2015. "A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-11, July.
    3. Rui Jiang & Mao-Bin Hu & Qing-Song Wu & Wei-Guo Song, 2017. "Traffic Dynamics of Bicycle Flow: Experiment and Modeling," Transportation Science, INFORMS, vol. 51(3), pages 998-1008, August.
    4. B. Jia & X.-G. Li & R. Jiang & Z.-Y. Gao, 2007. "Multi-value cellular automata model for mixed bicycle flow," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 56(3), pages 247-252, April.
    5. Thomas Götschi & Jan Garrard & Billie Giles-Corti, 2016. "Cycling as a Part of Daily Life: A Review of Health Perspectives," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 45-71, January.
    6. Jiang, Hang & Ma, Yongjian & Jiang, Lin & Chen, Guozhou & Wang, Dongwei, 2018. "Evaluation of the dispersion effect in through movement bicycles at signalized intersection via cellular automata simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 498(C), pages 138-147.
    7. Tang, Tie-Qiao & Luo, Xiao-Feng & Zhang, Jian & Chen, Liang, 2018. "Modeling electric bicycle’s lane-changing and retrograde behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1377-1386.
    8. Parkin, John & Rotheram, Jonathon, 2010. "Design speeds and acceleration characteristics of bicycle traffic for use in planning, design and appraisal," Transport Policy, Elsevier, vol. 17(5), pages 335-341, September.
    9. Jin, Sheng & Qu, Xiaobo & Zhou, Dan & Xu, Cheng & Ma, Dongfang & Wang, Dianhai, 2015. "Estimating cycleway capacity and bicycle equivalent unit for electric bicycles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 225-248.
    10. Rickert, M. & Nagel, K. & Schreckenberg, M. & Latour, A., 1996. "Two lane traffic simulations using cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 231(4), pages 534-550.
    11. Heather Kaths & Andreas Keler & Klaus Bogenberger, 2021. "Calibrating the Wiedemann 99 Car-Following Model for Bicycle Traffic," Sustainability, MDPI, vol. 13(6), pages 1-12, March.
    12. Tang, Tie-Qiao & Rui, Ying-Xu & Zhang, Jian & Shang, Hua-Yan, 2018. "A cellular automation model accounting for bicycle’s group behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1782-1797.
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