IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v105y2017icp212-234.html
   My bibliography  Save this article

On node models for high-dimensional road networks

Author

Listed:
  • Wright, Matthew A.
  • Gomes, Gabriel
  • Horowitz, Roberto
  • Kurzhanskiy, Alex A.

Abstract

Macroscopic traffic models are necessary for simulation and study of traffic’s complex macro-scale dynamics, and are often used by practitioners for road network planning, integrated corridor management, and other applications. These models have two parts: a link model, which describes traffic flow behavior on individual roads, and a node model, which describes behavior at road junctions. As the road networks under study become larger and more complex — nowadays often including arterial networks — the node model becomes more important. Despite their great importance to macroscopic models, however, only recently have node models had similar levels of attention as link models in the literature. This paper focuses on the first order node model and has two main contributions. First, we formalize the multi-commodity flow distribution at a junction as an optimization problem with all the necessary constraints. Most interesting here is the formalization of input flow priorities. Then, we discuss a very common “conservation of turning fractions” or “first-in-first-out” (FIFO) constraint, and how it often produces unrealistic spillback. This spillback occurs when, at a diverge, a queue develops for a movement that only a few lanes service, but FIFO requires that all lanes experience spillback from this queue. As we show, avoiding this unrealistic spillback while retaining FIFO in the node model requires complicated network topologies. Our second contribution is a “partial FIFO” mechanism that avoids this unrealistic spillback, and a (first-order) node model and solution algorithm that incorporates this mechanism. The partial FIFO mechanism is parameterized through intervals that describe how individual movements influence each other, can be intuitively described from physical lane geometry and turning movement rules, and allows tuning to describe a link as having anything between full FIFO and no FIFO. Excepting the FIFO constraint, the present node model also fits within the well-established “general class of first-order node models” for multi-commodity flows. Several illustrative examples are presented.

Suggested Citation

  • Wright, Matthew A. & Gomes, Gabriel & Horowitz, Roberto & Kurzhanskiy, Alex A., 2017. "On node models for high-dimensional road networks," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 212-234.
  • Handle: RePEc:eee:transb:v:105:y:2017:i:c:p:212-234
    DOI: 10.1016/j.trb.2017.09.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S019126151630008X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.trb.2017.09.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Flötteröd, Gunnar & Rohde, Jannis, 2011. "Operational macroscopic modeling of complex urban road intersections," Transportation Research Part B: Methodological, Elsevier, vol. 45(6), pages 903-922, July.
    2. Jabari, Saif Eddin, 2016. "Node modeling for congested urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 229-249.
    3. 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.
    4. 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.
    5. Smits, Erik-Sander & Bliemer, Michiel C.J. & Pel, Adam J. & van Arem, Bart, 2015. "A family of macroscopic node models," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 20-39.
    6. Raadsen, Mark P.H. & Bliemer, Michiel C.J. & Bell, Michael G.H., 2016. "An efficient and exact event-based algorithm for solving simplified first order dynamic network loading problems in continuous time," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 191-210.
    7. 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.
    8. Corthout, Ruben & Flötteröd, Gunnar & Viti, Francesco & Tampère, Chris M.J., 2012. "Non-unique flows in macroscopic first-order intersection models," Transportation Research Part B: Methodological, Elsevier, vol. 46(3), pages 343-359.
    9. Daganzo, Carlos F., 1994. "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transportation Research Part B: Methodological, Elsevier, vol. 28(4), pages 269-287, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Panda, Manoj & Ngoduy, Dong & Vu, Hai L., 2019. "Multiple model stochastic filtering for traffic density estimation on urban arterials," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 280-306.
    2. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "A stochastic dynamic network loading model for mixed traffic with autonomous and human-driven vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    3. Khodakaram Salimifard & Sara Bigharaz, 2022. "The multicommodity network flow problem: state of the art classification, applications, and solution methods," Operational Research, Springer, vol. 22(1), pages 1-47, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "A stochastic dynamic network loading model for mixed traffic with autonomous and human-driven vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    2. Flötteröd, G. & Osorio, C., 2017. "Stochastic network link transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 180-209.
    3. Himpe, Willem & Corthout, Ruben & Tampère, M.J. Chris, 2016. "An efficient iterative link transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 170-190.
    4. Ngoduy, D. & Hoang, N.H. & Vu, H.L. & Watling, D., 2016. "Optimal queue placement in dynamic system optimum solutions for single origin-destination traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 148-169.
    5. Jin, Wen-Long, 2017. "A Riemann solver for a system of hyperbolic conservation laws at a general road junction," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 21-41.
    6. Wang, Yi & Szeto, W.Y. & Han, Ke & Friesz, Terry L., 2018. "Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 370-394.
    7. Raadsen, Mark P.H. & Bliemer, Michiel C.J., 2019. "Continuous-time general link transmission model with simplified fanning, Part II: Event-based algorithm for networks," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 471-501.
    8. Yahyamozdarani, Raheleh & Tampère, Chris M.J., 2023. "The continuous signalized (COS) node model for dynamic traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 168(C), pages 56-80.
    9. Jabari, Saif Eddin, 2016. "Node modeling for congested urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 229-249.
    10. Bliemer, Michiel C.J. & Raadsen, Mark P.H., 2019. "Continuous-time general link transmission model with simplified fanning, Part I: Theory and link model formulation," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 442-470.
    11. Flötteröd, Gunnar & Rohde, Jannis, 2011. "Operational macroscopic modeling of complex urban road intersections," Transportation Research Part B: Methodological, Elsevier, vol. 45(6), pages 903-922, July.
    12. Bliemer, Michiel C.J. & Raadsen, Mark P.H., 2020. "Static traffic assignment with residual queues and spillback," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 303-319.
    13. Ge, Qian & Fukuda, Daisuke, 2019. "A macroscopic dynamic network loading model for multiple-reservoir system," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 502-527.
    14. Bliemer, Michiel C.J. & Raadsen, Mark P.H. & Smits, Erik-Sander & Zhou, Bojian & Bell, Michael G.H., 2014. "Quasi-dynamic traffic assignment with residual point queues incorporating a first order node model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 363-384.
    15. Carolina Osorio & Gunnar Flötteröd, 2015. "Capturing Dependency Among Link Boundaries in a Stochastic Dynamic Network Loading Model," Transportation Science, INFORMS, vol. 49(2), pages 420-431, May.
    16. Satsukawa, Koki & Wada, Kentaro & Watling, David, 2022. "Dynamic system optimal traffic assignment with atomic users: Convergence and stability," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 188-209.
    17. Osorio, Carolina & Flötteröd, Gunnar & Bierlaire, Michel, 2011. "Dynamic network loading: A stochastic differentiable model that derives link state distributions," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1410-1423.
    18. Jin, Wen-Long, 2015. "Continuous formulations and analytical properties of the link transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 88-103.
    19. Smits, Erik-Sander & Bliemer, Michiel C.J. & Pel, Adam J. & van Arem, Bart, 2015. "A family of macroscopic node models," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 20-39.
    20. Blumberg, Michal & Bar-Gera, Hillel, 2009. "Consistent node arrival order in dynamic network loading models," Transportation Research Part B: Methodological, Elsevier, vol. 43(3), pages 285-300, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:105:y:2017:i:c:p:212-234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.