IDEAS home Printed from https://ideas.repec.org/a/spr/eurjtl/v5y2016i1d10.1007_s13676-013-0037-x.html
   My bibliography  Save this article

A new class of doubly stochastic day-to-day dynamic traffic assignment models

Author

Listed:
  • Katharina Parry

    (Massey University
    Auckland University of Technology)

  • David P. Watling

    (University of Leeds)

  • Martin L. Hazelton

    (Massey University)

Abstract

Real-life systems are known to exhibit considerable day-to-day variability. A better understanding of such variability has increasing policy-relevance in the context of network reliability assessment and the design of intelligent transport systems. Conventional equilibrium models are ill-suited, because deterministic models such as these do not account for any kind of variability. At best, these types of models are restricted to finding a steady state of the mean flow patterns, they cannot capture the variance in flows as well. A more suitable alternative are stochastic day-to-day dynamic models studied by Cascetta in Trans Res 23:1–17, (1989). These types of traffic assignment models represent the traffic flows via a Markov process, where the current route flows are modelled as a function of previous traffic conditions. Day-to-day dynamic models differ from equilibrium models in that day-to-day changes in the system are modelled dependent on the time and thus allow for a far wider representation of traveller behaviour. However, to some degree they still suffer from some of the limitations of equilibrium analyses, in that while they permit variation they are still wedded to the concept of ‘stationarity’. In this paper, we show how these Markovian day-to-day dynamic traffic assignment models can be extended by replacing a subset of the fixed parameters in the Markov model with random processes. The resulting models are analogous to Cox process models. They are conditionally non-stationary given any realization of the parameter processes. We present numerical examples that demonstrate that this new class of doubly stochastic day-to-day traffic assignment models can indeed reproduce features such as the heteroscedasticity of traffic flows observed in real-life settings.

Suggested Citation

  • Katharina Parry & David P. Watling & Martin L. Hazelton, 2016. "A new class of doubly stochastic day-to-day dynamic traffic assignment models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 5-23, March.
  • Handle: RePEc:spr:eurjtl:v:5:y:2016:i:1:d:10.1007_s13676-013-0037-x
    DOI: 10.1007/s13676-013-0037-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13676-013-0037-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13676-013-0037-x?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. Martin L. Hazelton & David P. Watling, 2004. "Computation of Equilibrium Distributions of Markov Traffic-Assignment Models," Transportation Science, INFORMS, vol. 38(3), pages 331-342, August.
    2. Anders Brix & Peter J. Diggle, 2001. "Spatiotemporal prediction for log‐Gaussian Cox processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 823-841.
    3. Gary A. Davis & Nancy L. Nihan, 1993. "Large Population Approximations of a General Stochastic Traffic Assignment Model," Operations Research, INFORMS, vol. 41(1), pages 169-178, February.
    4. Carlos F. Daganzo & Yosef Sheffi, 1977. "On Stochastic Models of Traffic Assignment," Transportation Science, INFORMS, vol. 11(3), pages 253-274, August.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Cascetta, Ennio, 1989. "A stochastic process approach to the analysis of temporal dynamics in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 23(1), pages 1-17, February.
    7. Jesper Møller & Rasmus P. Waagepetersen, 2007. "Modern Statistics for Spatial Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 643-684, December.
    8. G. E. Cantarella & E. Cascetta, 1995. "Dynamic Processes and Equilibrium in Transportation Networks: Towards a Unifying Theory," Transportation Science, INFORMS, vol. 29(4), pages 305-329, November.
    9. Horowitz, Joel L., 1984. "The stability of stochastic equilibrium in a two-link transportation network," Transportation Research Part B: Methodological, Elsevier, vol. 18(1), pages 13-28, February.
    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. Paolo Delle Site, 2017. "On the Equivalence Between SUE and Fixed-Point States of Day-to-Day Assignment Processes with Serially-Correlated Route Choice," Networks and Spatial Economics, Springer, vol. 17(3), pages 935-962, September.
    2. Barroso, Joana Maia Fernandes & Albuquerque-Oliveira, João Lucas & Oliveira-Neto, Francisco Moraes, 2020. "Correlation analysis of day-to-day origin-destination flows and traffic volumes in urban networks," Journal of Transport Geography, Elsevier, vol. 89(C).
    3. Watling, David P. & Hazelton, Martin L., 2018. "Asymptotic approximations of transient behaviour for day-to-day traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 90-105.

    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. David Watling & Giulio Cantarella, 2015. "Model Representation & Decision-Making in an Ever-Changing World: The Role of Stochastic Process Models of Transportation Systems," Networks and Spatial Economics, Springer, vol. 15(3), pages 843-882, September.
    2. Paolo Delle Site, 2017. "On the Equivalence Between SUE and Fixed-Point States of Day-to-Day Assignment Processes with Serially-Correlated Route Choice," Networks and Spatial Economics, Springer, vol. 17(3), pages 935-962, September.
    3. He, Xiaozheng & Guo, Xiaolei & Liu, Henry X., 2010. "A link-based day-to-day traffic assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 597-608, May.
    4. Wei Nai & Zan Yang & Dan Li & Lu Liu & Yuting Fu & Yuao Guo, 2024. "Urban Day-to-Day Travel and Its Development in an Information Environment: A Review," Sustainability, MDPI, vol. 16(6), pages 1-29, March.
    5. Sun, Mingmei, 2023. "A day-to-day dynamic model for mixed traffic flow of autonomous vehicles and inertial human-driven vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    6. G. E. Cantarella & D. P. Watling, 2016. "Modelling road traffic assignment as a day-to-day dynamic, deterministic process: a unified approach to discrete- and continuous-time models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 69-98, March.
    7. Watling, David P. & Hazelton, Martin L., 2018. "Asymptotic approximations of transient behaviour for day-to-day traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 90-105.
    8. Zhu, Zheng & Mardan, Atabak & Zhu, Shanjiang & Yang, Hai, 2021. "Capturing the interaction between travel time reliability and route choice behavior based on the generalized Bayesian traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 48-64.
    9. Martin L. Hazelton & David P. Watling, 2004. "Computation of Equilibrium Distributions of Markov Traffic-Assignment Models," Transportation Science, INFORMS, vol. 38(3), pages 331-342, August.
    10. Hazelton, Martin L., 2022. "The emergence of stochastic user equilibria in day-to-day traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 102-112.
    11. Rambha, Tarun & Boyles, Stephen D., 2016. "Dynamic pricing in discrete time stochastic day-to-day route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 104-118.
    12. Jiayang Li & Zhaoran Wang & Yu Marco Nie, 2023. "Wardrop Equilibrium Can Be Boundedly Rational: A New Behavioral Theory of Route Choice," Papers 2304.02500, arXiv.org, revised Feb 2024.
    13. David Watling, 2002. "A Second Order Stochastic Network Equilibrium Model, I: Theoretical Foundation," Transportation Science, INFORMS, vol. 36(2), pages 149-166, May.
    14. Kumar, Amit & Peeta, Srinivas, 2015. "A day-to-day dynamical model for the evolution of path flows under disequilibrium of traffic networks with fixed demand," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 235-256.
    15. Parry, Katharina & Hazelton, Martin L., 2013. "Bayesian inference for day-to-day dynamic traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 104-115.
    16. Xiaomei Zhao & Chunhua Wan & Jun Bi, 2019. "Day-to-Day Assignment Models and Traffic Dynamics Under Information Provision," Networks and Spatial Economics, Springer, vol. 19(2), pages 473-502, June.
    17. Bie, Jing & Lo, Hong K., 2010. "Stability and attraction domains of traffic equilibria in a day-to-day dynamical system formulation," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 90-107, January.
    18. Wang, Jian & He, Xiaozheng & Peeta, Srinivas, 2016. "Sensitivity analysis based approximation models for day-to-day link flow evolution process," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 35-53.
    19. Watling, David, 1999. "Stability of the stochastic equilibrium assignment problem: a dynamical systems approach," Transportation Research Part B: Methodological, Elsevier, vol. 33(4), pages 281-312, May.
    20. Meneguzzer, Claudio, 2022. "Day-to-day dynamics in a simple traffic network with mixed direct and contrarian route choice behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).

    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:spr:eurjtl:v:5:y:2016:i:1:d:10.1007_s13676-013-0037-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.