IDEAS home Printed from https://ideas.repec.org/p/ucr/wpaper/201612.html
   My bibliography  Save this paper

A Model of Rush-Hour Traffic Dynamics in an Isotropic Downtown Area

Author

Listed:
  • Richard Arnott

    (Department of Economics, University of California Riverside)

  • Anatolii Kokoza

    (Department of Economics, University of Arizona)

  • Mehdi Naji

    (Department of Money and Foreign Currencies, Money and Banking Research Institute)

Abstract

For a quarter century, a top priority in transportation economic theory has been to develop models of rush-hour traffic dynamics that incorporate hypercongestion – situations of heavy congestion where throughput decreases as traffic density increases. Unfortunately, even the simplest models along these lines appear to be analytically intractable, and none of the models that have made approximations in order to achieve tractability has gained widespread acceptance. This paper takes a different tack focusing on a special case – the isotropic model with identical commuters and the α − β − γ cost function – for which an analytical solution is possible. A complete, closed-form solution is presented for the no-toll equilibrium in which departures and arrivals occur in masses, and the solution for the social optimum is fully characterized.

Suggested Citation

  • Richard Arnott & Anatolii Kokoza & Mehdi Naji, 2016. "A Model of Rush-Hour Traffic Dynamics in an Isotropic Downtown Area," Working Papers 201612, University of California at Riverside, Department of Economics.
  • Handle: RePEc:ucr:wpaper:201612
    as

    Download full text from publisher

    File URL: https://economics.ucr.edu/repec/ucr/wpaper/201612.pdf
    File Function: First version, 2016
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fosgerau, Mogens & Small, Kenneth A., 2013. "Hypercongestion in downtown metropolis," Journal of Urban Economics, Elsevier, vol. 76(C), pages 122-134.
    2. Arnott, Richard, 2013. "A bathtub model of downtown traffic congestion," Journal of Urban Economics, Elsevier, vol. 76(C), pages 110-121.
    3. Kenneth Small, 2015. "The Bottleneck Model: An Assessment and Interpretation," Working Papers 141506, University of California-Irvine, Department of Economics.
    4. Arnott, Richard & Inci, Eren, 2010. "The stability of downtown parking and traffic congestion," Journal of Urban Economics, Elsevier, vol. 68(3), pages 260-276, November.
    5. Carson E. Agnew, 1976. "Dynamic Modeling and Control of Congestion-Prone Systems," Operations Research, INFORMS, vol. 24(3), pages 400-419, June.
    6. Small, Kenneth A., 2015. "The bottleneck model: An assessment and interpretation," Economics of Transportation, Elsevier, vol. 4(1), pages 110-117.
    7. Fosgerau, Mogens, 2015. "Congestion in the bathtub," Economics of Transportation, Elsevier, vol. 4(4), pages 241-255.
    8. Geroliminis, Nikolas & Daganzo, Carlos F., 2008. "Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 759-770, November.
    9. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-260, May.
    10. Nikolas Geroliminis & David M. Levinson, 2009. "Cordon Pricing Consistent with the Physics of Overcrowding," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 219-240, Springer.
    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. Arnott, Richard & Kokoza, Anatolii & Naji, Mehdi, 2016. "Equilibrium traffic dynamics in a bathtub model: A special case," Economics of Transportation, Elsevier, vol. 7, pages 38-52.
    2. Richard Arnott & Anatolii Kokoza & Mehdi Naji, 2015. "A Model of Rush-Hour Traffic in an Isotropic Downtown Area," Working Papers 201511, University of California at Riverside, Department of Economics.
    3. Amirgholy, Mahyar & Gao, H. Oliver, 2017. "Modeling the dynamics of congestion in large urban networks using the macroscopic fundamental diagram: User equilibrium, system optimum, and pricing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 215-237.
    4. Liu, Wei & Geroliminis, Nikolas, 2016. "Modeling the morning commute for urban networks with cruising-for-parking: An MFD approach," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 470-494.
    5. Fosgerau, Mogens, 2015. "Congestion in the bathtub," Economics of Transportation, Elsevier, vol. 4(4), pages 241-255.
    6. Arnott, Richard, 2013. "A bathtub model of downtown traffic congestion," Journal of Urban Economics, Elsevier, vol. 76(C), pages 110-121.
    7. Bao, Yue & Verhoef, Erik T. & Koster, Paul, 2021. "Leaving the tub: The nature and dynamics of hypercongestion in a bathtub model with a restricted downstream exit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    8. Amirgholy, Mahyar & Shahabi, Mehrdad & Gao, H. Oliver, 2017. "Optimal design of sustainable transit systems in congested urban networks: A macroscopic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 261-285.
    9. Li, Zhi-Chun & Huang, Hai-Jun & Yang, Hai, 2020. "Fifty years of the bottleneck model: A bibliometric review and future research directions," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 311-342.
    10. Kathrin Goldmann & Gernot Sieg, 2020. "Quantifying the phantom jam externality: The case of an Autobahn section in Germany," Working Papers 30, Institute of Transport Economics, University of Muenster.
    11. Frascaria, Dario & Olver, Neil & Verhoef, Erik, 2020. "Emergent hypercongestion in Vickrey bottleneck networks," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 523-538.
    12. Geroliminis, Nikolas, 2015. "Cruising-for-parking in congested cities with an MFD representation," Economics of Transportation, Elsevier, vol. 4(3), pages 156-165.
    13. Kathrin Goldmann & Gernot Sieg, 2018. "Economic implications of phantom traffic jams: Evidence from traffic experiments," Working Papers 26, Institute of Transport Economics, University of Muenster.
    14. Lamotte, Raphaël & Geroliminis, Nikolas, 2018. "The morning commute in urban areas with heterogeneous trip lengths," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 794-810.
    15. Arnott, Richard & Buli, Joshua, 2018. "Solving for equilibrium in the basic bathtub model," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 150-175.
    16. Dantsuji, Takao & Takayama, Yuki & Fukuda, Daisuke, 2023. "Perimeter control in a mixed bimodal bathtub model," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 267-291.
    17. Yildirimoglu, Mehmet & Ramezani, Mohsen, 2020. "Demand management with limited cooperation among travellers: A doubly dynamic approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 267-284.
    18. Daganzo, Carlos F. & Lehe, Lewis J., 2015. "Distance-dependent congestion pricing for downtown zones," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 89-99.
    19. Daganzo, Carlos F & Lehe, Lewis J, 2014. "Distance-dependent Congestion Pricing for Downtown Zones," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt9vz1b9rs, Institute of Transportation Studies, UC Berkeley.
    20. Lehe, Lewis J., 2017. "Downtown tolls and the distribution of trip lengths," Economics of Transportation, Elsevier, vol. 11, pages 23-32.

    More about this item

    Keywords

    equilibrium; rush hour; traffic congestion;
    All these keywords.

    JEL classification:

    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ucr:wpaper:201612. 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: Kelvin Mac (email available below). General contact details of provider: https://edirc.repec.org/data/deucrus.html .

    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.