IDEAS home Printed from https://ideas.repec.org/a/taf/transr/v37y2017i1p56-78.html
   My bibliography  Save this article

Genetics of traffic assignment models for strategic transport planning

Author

Listed:
  • Michiel C. J. Bliemer
  • Mark P. H. Raadsen
  • Luuk J. N. Brederode
  • Michael G. H. Bell
  • Luc J. J. Wismans
  • Mike J. Smith

Abstract

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.

Suggested Citation

  • Michiel C. J. Bliemer & Mark P. H. Raadsen & Luuk J. N. Brederode & Michael G. H. Bell & Luc J. J. Wismans & Mike J. Smith, 2017. "Genetics of traffic assignment models for strategic transport planning," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 56-78, January.
    • Handle: RePEc:taf:transr:v:37:y:2017:i:1:p:56-78
    DOI: 10.1080/01441647.2016.1207211
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01441647.2016.1207211
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01441647.2016.1207211?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. Guido Gentile, 2010. "The General Link Transmission Model for Dynamic Network Loading and a Comparison with the DUE Algorithm," Chapters, in: Chris M.J. Tampere & Francesco Viti & Lambertus H. (Ben) Immers (ed.), New Developments in Transport Planning, chapter 8, Edward Elgar Publishing.
    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. Zhang, Yachao & Xie, Shiwei & Shu, Shengwen, 2022. "Multi-stage robust optimization of a multi-energy coupled system considering multiple uncertainties," Energy, Elsevier, vol. 238(PC).
    2. Wei Huang & Guangming Xu & Hong K. Lo, 2020. "Pareto-Optimal Sustainable Transportation Network Design under Spatial Queuing," Networks and Spatial Economics, Springer, vol. 20(3), pages 637-673, September.
    3. Raadsen, Mark P.H. & Bliemer, Michiel C.J., 2019. "Steady-state link travel time methods: Formulation, derivation, classification, and unification," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 167-191.
    4. Brederode, Luuk & Pel, Adam & Wismans, Luc & Rijksen, Bernike & Hoogendoorn, Serge, 2023. "Travel demand matrix estimation for strategic road traffic assignment models with strict capacity constraints and residual queues," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 1-31.
    5. Raadsen, Mark P.H. & Bliemer, Michiel C.J., 2023. "General solution scheme for the static link transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 108-135.
    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. 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.
    8. Ke Han & Gabriel Eve & Terry L. Friesz, 2019. "Computing Dynamic User Equilibria on Large-Scale Networks with Software Implementation," Networks and Spatial Economics, Springer, vol. 19(3), pages 869-902, September.
    9. Du, Muqing & Tan, Heqing & Chen, Anthony, 2021. "A faster path-based algorithm with Barzilai-Borwein step size for solving stochastic traffic equilibrium models," European Journal of Operational Research, Elsevier, vol. 290(3), pages 982-999.
    10. Zhou, Zhe & Zhang, Xuan & Guo, Qinglai & Sun, Hongbin, 2021. "Analyzing power and dynamic traffic flows in coupled power and transportation networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    11. Babak Javani & Abbas Babazadeh, 2020. "Path-Based Dynamic User Equilibrium Model with Applications to Strategic Transportation Planning," Networks and Spatial Economics, Springer, vol. 20(2), pages 329-366, June.
    12. Raadsen, Mark P.H. & Bliemer, Michiel C.J. & Bell, Michael G.H., 2020. "Aggregation, disaggregation and decomposition methods in traffic assignment: historical perspectives and new trends," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 199-223.

    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. Raadsen, Mark P.H. & Bliemer, Michiel C.J., 2019. "Steady-state link travel time methods: Formulation, derivation, classification, and unification," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 167-191.
    2. 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.
    3. 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.
    4. Gentile, Guido, 2016. "Solving a Dynamic User Equilibrium model based on splitting rates with Gradient Projection algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 120-147.
    5. Jabari, Saif Eddin, 2016. "Node modeling for congested urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 229-249.
    6. Raadsen, Mark P.H. & Bliemer, Michiel C.J., 2023. "General solution scheme for the static link transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 108-135.
    7. 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.
    8. van der Gun, Jeroen P.T. & Pel, Adam J. & van Arem, Bart, 2017. "Extending the Link Transmission Model with non-triangular fundamental diagrams and capacity drops," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 154-178.
    9. 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.
    10. 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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:transr:v:37:y:2017:i:1:p:56-78. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TTRV20 .

    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.