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Bounded acceleration close to fixed and moving bottlenecks

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  • Leclercq, Ludovic

Abstract

The aim of this paper is to study how to represent bounded acceleration close to fixed and moving bottlenecks in the "Lighthill, Whitham and Richards" (LWR) framework. This generalizes the existing works on bounded acceleration which are devoted to homogeneous road sections. First an overview of the existing research is proposed, and then the specific problem of bottlenecks is examined. The concept of a transition area upstream of the bottlenecks is proposed to precisely represent vehicle kinematics during the acceleration phase. The last part of the paper deals with the numerical resolution of the bounded acceleration model close to bottlenecks and presents numerical examples for a fixed and a moving bottleneck.

Suggested Citation

  • Leclercq, Ludovic, 2007. "Bounded acceleration close to fixed and moving bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 309-319, March.
    • Handle: RePEc:eee:transb:v:41:y:2007:i:3:p:309-319
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    References listed on IDEAS

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    1. Daganzo, Carlos F., 1995. "The cell transmission model, part II: Network traffic," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 79-93, April.
    2. Newell, G. F., 1998. "A moving bottleneck," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 531-537, November.
    3. Daganzo, Carlos F. & Laval, Jorge A., 2005. "On the numerical treatment of moving bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 39(1), pages 31-46, January.
    4. W.-L. Jin & H. M. Zhang, 2003. "The Inhomogeneous Kinematic Wave Traffic Flow Model as a Resonant Nonlinear System," Transportation Science, INFORMS, vol. 37(3), pages 294-311, August.
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    Cited by:

    1. Wang, Jiawen & Zou, Linzhi & Zhao, Jing & Wang, Xinwei, 2024. "Dynamic capacity drop propagation in incident-affected networks: Traffic state modeling with SIS-CTM," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    2. Leclercq, Ludovic & Ladino, Andres & Becarie, Cécile, 2021. "Enforcing optimal routing through dynamic avoidance maps," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 118-137.
    3. Rifki, Omar & Chiabaut, Nicolas & Solnon, Christine, 2020. "On the impact of spatio-temporal granularity of traffic conditions on the quality of pickup and delivery optimal tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    4. Mohammadian, Saeed & Zheng, Zuduo & Haque, Md. Mazharul & Bhaskar, Ashish, 2021. "Performance of continuum models for realworld traffic flows: Comprehensive benchmarking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 132-167.
    5. Costeseque, Guillaume & Lebacque, Jean-Patrick, 2014. "A variational formulation for higher order macroscopic traffic flow models: Numerical investigation," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 112-133.
    6. Jin, Wen-Long, 2017. "A first-order behavioral model of capacity drop," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 438-457.
    7. Jin, Wen-Long & Laval, Jorge, 2018. "Bounded acceleration traffic flow models: A unified approach," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 1-18.
    8. Krug, Jean & Burianne, Arthur & Bécarie, Cécile & Leclercq, Ludovic, 2021. "Refining trip starting and ending locations when estimating travel-demand at large urban scale," Journal of Transport Geography, Elsevier, vol. 93(C).

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