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A generic class of first order node models for dynamic macroscopic simulation of traffic flows

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  • Tampère, Chris M.J.
  • Corthout, Ruben
  • Cattrysse, Dirk
  • Immers, Lambertus H.

Abstract

Node models for macroscopic simulation have attracted relatively little attention in the literature. Nevertheless, in dynamic network loading (DNL) models for congested road networks, node models are as important as the extensively studied link models. This paper provides an overview of macroscopic node models found in the literature, explaining both their contributions and shortcomings. A formulation defining a generic class of first order macroscopic node models is presented, satisfying a list of requirements necessary to produce node models with realistic, consistent results. Defining a specific node model instance of this class requires the specification of a supply constraint interaction rule and (optionally) node supply constraints. Following this theoretical discussion, specific macroscopic node model instances for unsignalized and signalized intersections are proposed. These models apply an oriented capacity proportional distribution of the available supply over the incoming links of a node. A computationally efficient algorithm to solve the node models exactly is included.

Suggested Citation

  • Tampère, Chris M.J. & Corthout, Ruben & Cattrysse, Dirk & Immers, Lambertus H., 2011. "A generic class of first order node models for dynamic macroscopic simulation of traffic flows," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 289-309, January.
  • Handle: RePEc:eee:transb:v:45:y:2011:i:1:p:289-309
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    1. Troutbeck, Rod J. & Kako, Soichiro, 1999. "Limited priority merge at unsignalized intersections," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(3-4), pages 291-304, April.
    2. 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.
    3. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 281-287, August.
    4. Bin Ran & David E. Boyce & Larry J. LeBlanc, 1993. "A New Class of Instantaneous Dynamic User-Optimal Traffic Assignment Models," Operations Research, INFORMS, vol. 41(1), pages 192-202, February.
    5. Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2007. "Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1114-1138, December.
    6. Jin, W. L. & Zhang, H. M., 2003. "On the distribution schemes for determining flows through a merge," Transportation Research Part B: Methodological, Elsevier, vol. 37(6), pages 521-540, July.
    7. Ansorge, Rainer, 1990. "What does the entropy condition mean in traffic flow theory?," Transportation Research Part B: Methodological, Elsevier, vol. 24(2), pages 133-143, April.
    8. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part III: Multi-destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 305-313, August.
    9. Jin, Wen-Long, 2010. "Continuous kinematic wave models of merging traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1084-1103, September.
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