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Multiclass Traffic Flow Dynamics: An Endogenous Model

Author

Listed:
  • Kai Yuan

    (Hefei University of Technology, Hefei 230009, China)

  • Hong K. Lo

    (Hong Kong University of Science and Technology, Kowloon, Hong Kong)

Abstract

Vehicles on roads can be distinguished, each defined by its own set of properties (e.g., fleet length and free-flow speed). The traffic states on roads can be attributed to the longitudinal heterogeneity in vehicles. Vehicles slower than prevailing vehicles are defined as moving bottlenecks. On a multilane road section with multiple vehicle types, slower vehicles create moving bottlenecks and induce overtaking by faster vehicles so as to maintain their higher desired speed. The influence of single-class moving bottlenecks has been studied in the past. However, the impacts of multiple classes of moving bottlenecks have not yet been fully explored. This paper categorizes vehicles into passenger cars, medium trucks, and heavy trucks. By defining medium trucks and heavy trucks as moving bottlenecks, we develop analytical formulas for the fundamental diagram on a multilane road section with heterogeneous moving bottlenecks. The formula confirms that the composition of traffic and the longest truck platoon length influence the fundamental diagram. We then conduct simulations using a first-order kinematic wave model in Lagrangian coordinates to validate the fundamental diagram developed with the analytical formula and obtain promising results. This study provides fundamental knowledge for multiclass traffic modeling and multilane traffic operations.

Suggested Citation

  • Kai Yuan & Hong K. Lo, 2021. "Multiclass Traffic Flow Dynamics: An Endogenous Model," Transportation Science, INFORMS, vol. 55(2), pages 456-474, March.
    • Handle: RePEc:inm:ortrsc:v:55:y:2021:i:2:p:456-474
    DOI: 10.1287/trsc.2020.1015
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    References listed on IDEAS

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    Cited by:

    1. Cheng, Qixiu & Lin, Yuqian & Zhou, Xuesong (Simon) & Liu, Zhiyuan, 2024. "Analytical formulation for explaining the variations in traffic states: A fundamental diagram modeling perspective with stochastic parameters," European Journal of Operational Research, Elsevier, vol. 312(1), pages 182-197.

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