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Vehicle Longitudinal Control and Traffic Stream Modeling

Author

Listed:
  • Daiheng Ni

    (Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003)

  • John D. Leonard

    (School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Chaoqun Jia

    (Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003)

  • Jianqiang Wang

    (Department of Automotive Engineering, Tsinghua University, 100084 Beijing, China)

Abstract

A simple yet efficient traffic flow model, in particular one that describes vehicle longitudinal operational control and further characterizes a traffic flow fundamental diagram, is always desirable. Though many models have been proposed in the past with each having its own merits, research in this area is far from conclusive. This paper contributes a new model, i.e., the longitudinal control model, to the arsenal with a unique set of properties. The model is suited for a variety of transportation applications, among which a concrete example is provided in this paper.

Suggested Citation

  • Daiheng Ni & John D. Leonard & Chaoqun Jia & Jianqiang Wang, 2016. "Vehicle Longitudinal Control and Traffic Stream Modeling," Transportation Science, INFORMS, vol. 50(3), pages 1016-1031, August.
    • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:3:p:1016-1031
    DOI: 10.1287/trsc.2015.0614
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    References listed on IDEAS

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    Cited by:

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    2. 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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    4. Qin, Yanyan & Liu, Mingxuan & Hao, Wei, 2024. "Energy-optimal car-following model for connected automated vehicles considering traffic flow stability," Energy, Elsevier, vol. 298(C).

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