IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v36y2002i8p671-681.html
   My bibliography  Save this article

Risk-averse user equilibrium traffic assignment: an application of game theory

Author

Listed:
  • Bell, Michael G. H.
  • Cassir, Chris

Abstract

No abstract is available for this item.

Suggested Citation

  • Bell, Michael G. H. & Cassir, Chris, 2002. "Risk-averse user equilibrium traffic assignment: an application of game theory," Transportation Research Part B: Methodological, Elsevier, vol. 36(8), pages 671-681, September.
    • Handle: RePEc:eee:transb:v:36:y:2002:i:8:p:671-681
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(01)00022-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Garcia, Alfredo & Reaume, Daniel & Smith, Robert L., 2000. "Fictitious play for finding system optimal routings in dynamic traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 147-156, February.
    2. Hall, Randolph W., 1983. "Travel outcome and performance: The effect of uncertainty on accessibility," Transportation Research Part B: Methodological, Elsevier, vol. 17(4), pages 275-290, August.
    3. Bell, Michael G. H., 2000. "A game theory approach to measuring the performance reliability of transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 533-545, August.
    Full references (including those not matched with items on IDEAS)

    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. Hu Shao & William Lam & Mei Tam, 2006. "A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand," Networks and Spatial Economics, Springer, vol. 6(3), pages 173-204, September.
    2. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    3. Dusica Joksimovic & Erik T. Verhoef & Michiel Bliemer, 2005. "Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach," ERSA conference papers ersa05p430, European Regional Science Association.
    4. Hadas, Yuval & Gnecco, Giorgio & Sanguineti, Marcello, 2017. "An approach to transportation network analysis via transferable utility games," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 120-143.
    5. Agustín Santos & Antonio Fernández Anta & Luis López Fernández, 2013. "Quid Pro Quo: A Mechanism for Fair Collaboration in Networked Systems," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-15, September.
    6. Szeto, W.Y. & Farahani, R.Z. & Sumalee, Agachai, 2017. "Link-based multi-class hazmat routing-scheduling problem: A multiple demon approach," European Journal of Operational Research, Elsevier, vol. 261(1), pages 337-354.
    7. Shao, Hu & Lam, William H.K. & Sumalee, Agachai & Chen, Anthony & Hazelton, Martin L., 2014. "Estimation of mean and covariance of peak hour origin–destination demands from day-to-day traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 52-75.
    8. Bell, Michael G.H. & Kurauchi, Fumitaka & Perera, Supun & Wong, Walter, 2017. "Investigating transport network vulnerability by capacity weighted spectral analysis," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 251-266.
    9. Zhaoqi Zang & Richard Batley & Xiangdong Xu & David Z. W. Wang, 2022. "On the value of distribution tail in the valuation of travel time variability," Papers 2207.06293, arXiv.org, revised Dec 2023.
    10. Alan T. Murray & Timothy C. Matisziw & Tony H. Grubesic, 2008. "A Methodological Overview of Network Vulnerability Analysis," Growth and Change, Wiley Blackwell, vol. 39(4), pages 573-592, December.
    11. Rodríguez-Núñez, Eduardo & García-Palomares, Juan Carlos, 2014. "Measuring the vulnerability of public transport networks," Journal of Transport Geography, Elsevier, vol. 35(C), pages 50-63.
    12. Sjoerd van der Spoel & Chintan Amrit & Jos van Hillegersberg, 2017. "Predictive analytics for truck arrival time estimation: a field study at a European distribution centre," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5062-5078, September.
    13. Michael W. Levin & Melissa Duell & S. Travis Waller, 2020. "Arrival Time Reliability in Strategic User Equilibrium," Networks and Spatial Economics, Springer, vol. 20(3), pages 803-831, September.
    14. Berger, Ulrich, 2005. "Fictitious play in 2 x n games," Journal of Economic Theory, Elsevier, vol. 120(2), pages 139-154, February.
    15. Swenson, Brian & Murray, Ryan & Kar, Soummya, 2020. "Regular potential games," Games and Economic Behavior, Elsevier, vol. 124(C), pages 432-453.
    16. Nima Haghighi & S. Kiavash Fayyaz & Xiaoyue Cathy Liu & Tony H. Grubesic & Ran Wei, 2018. "A Multi-Scenario Probabilistic Simulation Approach for Critical Transportation Network Risk Assessment," Networks and Spatial Economics, Springer, vol. 18(1), pages 181-203, March.
    17. Lu, Chung-Cheng & Liu, Jiangtao & Qu, Yunchao & Peeta, Srinivas & Rouphail, Nagui M. & Zhou, Xuesong, 2016. "Eco-system optimal time-dependent flow assignment in a congested network," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 217-239.
    18. Sugiura, Satoshi & Chen, Anthony, 2021. "Vulnerability analysis of cut-capacity structure and OD demand using Gomory-Hu tree method," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 111-127.
    19. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    20. Wang, Judith Y.T. & Ehrgott, Matthias & Chen, Anthony, 2014. "A bi-objective user equilibrium model of travel time reliability in a road network," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 4-15.

    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:eee:transb:v:36:y:2002:i:8:p:671-681. 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.