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Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model

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  • Hou, Xianlei
  • Zhang, Rui
  • Yang, Minghui
  • Cheng, Shida

Abstract

Using traffic marking to separate non-motorized lane from the adjacent motorized lane is a common traffic design method for urban road segments. With the increase in non-motorized vehicle flow, illegal lane-changing occurs frequently, which leads to more serious conflict among road users. The study of the behavior characteristics of non-motorized illegal lane-changing on road segments, and establishing a microscopic simulation model can be used as a theoretical support and analysis tool for the design of non-motorized lane. This paper takes non-motorized vehicles as the research object to study lane-changing behavior characteristics. Then, the K-means clustering algorithm is used to classify riding styles into three types: risker, opportunist, and prudent. The micro-behavioral characteristics of riders with different riding styles are analyzed. Next, a three-layer model framework composed of perceptual, decision-making, and social force model is established. The logit model is used in the decision-making model to predict the probability of non-motorized vehicles crossing the line. Different riding styles are considered in the social force, and a virtual boundary force is introduced to describe lane-changing behavior. Subsequently, parameters are calibrated and the model is validated in various ways. Finally, the proposed model is used to conduct simulation experiments to explore the renovation scheme of the non-motorized lane. The results show that the proposed model can reproduce the traffic operation in the real scenario.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:633:y:2024:i:c:s0378437123009706
    DOI: 10.1016/j.physa.2023.129415
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    References listed on IDEAS

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    1. Mai, Tien & Fosgerau, Mogens & Frejinger, Emma, 2015. "A nested recursive logit model for route choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 100-112.
    2. Hu, Xiaojian & Qiao, Longqi & Hao, Xiatong & Lin, Chenxi & Liu, Tenghui, 2022. "Research on the impact of entry points on urban arterial roads in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    3. Elisabeth Rubie & Narelle Haworth & Divera Twisk & Naohide Yamamoto, 2020. "Influences on lateral passing distance when motor vehicles overtake bicycles: a systematic literature review," Transport Reviews, Taylor & Francis Journals, vol. 40(6), pages 754-773, November.
    4. Grigoropoulos, Georgios & Leonhardt, Axel & Kaths, Heather & Junghans, Marek & Baier, Michael M. & Busch, Fritz, 2022. "Traffic flow at signalized intersections with large volumes of bicycle traffic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 464-483.
    5. Vasic, Jelena & Ruskin, Heather J., 2012. "Cellular automata simulation of traffic including cars and bicycles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2720-2729.
    6. Yan Liu & Chuanyun Fu & Wei Wang, 2021. "Modeling duration of overtaking between non-motorized vehicles: A nonparametric survival analysis based approach," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-14, January.
    7. Bi, Hui & Li, Aoyong & Zhu, He & Ye, Zhirui, 2023. "Bicycle safety outside the crosswalks: Investigating cyclists' risky street-crossing behavior and its relationship with built environment," Journal of Transport Geography, Elsevier, vol. 108(C).
    8. Kanagaraj, Venkatesan & Treiber, Martin, 2018. "Self-driven particle model for mixed traffic and other disordered flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1-11.
    9. Ni, Ying & Li, Yixin & Yuan, Yufei & Sun, Jian, 2023. "An operational simulation framework for modelling the multi-interaction of two-wheelers on mixed-traffic road segments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    10. 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.
    11. Hu, Xiaojian & Lin, Chenxi & Hao, Xiatong & Lu, RuiYing & Liu, TengHui, 2021. "Influence of tidal lane on traffic breakdown and spatiotemporal congested patterns at moving bottleneck in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    Full references (including those not matched with items on IDEAS)

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