IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v29y1995i3p155-170.html
   My bibliography  Save this article

A model for the dynamic system optimum traffic assignment problem

Author

Listed:
  • Ghali, M. O.
  • Smith, M. J.

Abstract

We describe a deterministic queueing assignment model which seeks to reduce total travel delays in a road traffic network by routeing drivers according to the total delay caused on each link (the local marginal delay). The model is approximate and is applicable to networks with many origin-destination pairs and many bottlenecks. Optimality of the solution determined by the model is discussed. It is particularly shown that, unlike in the steady state (Dafermos and Sparrow, 1969), reducing total travel times by using the local marginal delay will not generally result in an optimal solution. Results are provided for two networks.

Suggested Citation

  • Ghali, M. O. & Smith, M. J., 1995. "A model for the dynamic system optimum traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 29(3), pages 155-170, June.
    • Handle: RePEc:eee:transb:v:29:y:1995:i:3:p:155-170
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0191-2615(94)00024-T
    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. Deepak K. Merchant & George L. Nemhauser, 1978. "Optimality Conditions for a Dynamic Traffic Assignment Model," Transportation Science, INFORMS, vol. 12(3), pages 200-207, August.
    2. Malachy Carey, 1987. "Optimal Time-Varying Flows on Congested Networks," Operations Research, INFORMS, vol. 35(1), pages 58-69, February.
    3. Smith, M. J., 1993. "A new dynamic traffic model and the existence and calculation of dynamic user equilibria on congested capacity-constrained road networks," Transportation Research Part B: Methodological, Elsevier, vol. 27(1), pages 49-63, February.
    4. Malachy Carey, 1986. "A Constraint Qualification for a Dynamic Traffic Assignment Model," Transportation Science, INFORMS, vol. 20(1), pages 55-58, February.
    5. MERCHANT, Deepak K. & NEMHAUSER, George L., 1978. "Optimality conditions for a dynamic traffic assignment model," LIDAM Reprints CORE 345, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    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, Chao & Osorio, Carolina & Flötteröd, Gunnar, 2017. "Efficient calibration techniques for large-scale traffic simulators," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 214-239.
    2. Nie, Yu (Marco), 2011. "A cell-based Merchant-Nemhauser model for the system optimum dynamic traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 329-342, February.
    3. Lu, Gongyuan & Nie, Yu(Marco) & Liu, Xiaobo & Li, Denghui, 2019. "Trajectory-based traffic management inside an autonomous vehicle zone," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 76-98.
    4. 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.
    5. Lu, Jiawei & Nie, Qinghui & Mahmoudi, Monirehalsadat & Ou, Jishun & Li, Chongnan & Zhou, Xuesong Simon, 2022. "Rich arc routing problem in city logistics: Models and solution algorithms using a fluid queue-based time-dependent travel time representation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 143-182.
    6. André de Palma & Robin Lindsey, 2009. "Traffic Congestion Pricing Methods and Technologies," Working Papers hal-00414526, HAL.
    7. 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.
    8. Mounce, Richard, 2006. "Convergence in a continuous dynamic queueing model for traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 779-791, November.
    9. Song, Ying & Miller, Harvey J. & Stempihar, Jeff & Zhou, Xuesong, 2017. "Green accessibility: Estimating the environmental costs of network-time prisms for sustainable transportation planning," Journal of Transport Geography, Elsevier, vol. 64(C), pages 109-119.
    10. Yan-Qun Jiang & S.C. Wong & Peng Zhang & Keechoo Choi, 2017. "Dynamic Continuum Model with Elastic Demand for a Polycentric Urban City," Transportation Science, INFORMS, vol. 51(3), pages 931-945, August.
    11. Shen, Wei & Zhang, H.M., 2009. "On the morning commute problem in a corridor network with multiple bottlenecks: Its system-optimal traffic flow patterns and the realizing tolling scheme," Transportation Research Part B: Methodological, Elsevier, vol. 43(3), pages 267-284, March.
    12. Li, Jun & Fujiwara, Okitsugu & Kawakami, Shogo, 2000. "A reactive dynamic user equilibrium model in network with queues," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 605-624, November.
    13. Long, Jiancheng & Wang, Chao & Szeto, W.Y., 2018. "Dynamic system optimum simultaneous route and departure time choice problems: Intersection-movement-based formulations and comparisons," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 166-206.
    14. Shen, Wei & Zhang, H. Michael, 2009. "On the Morning Commute Problem in a Corridor Network with Multiple Bottlenecks: Its System-optimal Traffic Flow Patterns and the Realizing Tolling Scheme," Institute of Transportation Studies, Working Paper Series qt9bs815sq, Institute of Transportation Studies, UC Davis.
    15. Zhu, Feng & Ukkusuri, Satish V., 2017. "Efficient and fair system states in dynamic transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 272-289.
    16. Fusco, G. & Bielli, M. & Cipriani, E. & Gori, S. & Nigro, M., 2013. "Signal settings synchronization and dynamic traffic modelling," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 53, pages 1-7.
    17. Shen, Wei & Zhang, H.M., 2014. "System optimal dynamic traffic assignment: Properties and solution procedures in the case of a many-to-one network," Transportation Research Part B: Methodological, Elsevier, vol. 65(C), pages 1-17.
    18. Zhang, Pinchao & Qian, Sean, 2020. "Path-based system optimal dynamic traffic assignment: A subgradient approach," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 41-63.
    19. Zhao, Chuan-Lin & Leclercq, Ludovic, 2018. "Graphical solution for system optimum dynamic traffic assignment with day-based incentive routing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 87-100.
    20. Rinaldi, Marco, 2018. "Controllability of transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 381-406.

    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. S. Waller & Athanasios Ziliaskopoulos, 2006. "A Combinatorial user optimal dynamic traffic assignment algorithm," Annals of Operations Research, Springer, vol. 144(1), pages 249-261, April.
    2. Tong, C. O. & Wong, S. C., 2000. "A predictive dynamic traffic assignment model in congested capacity-constrained road networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 625-644, November.
    3. Nie, Yu (Marco), 2011. "A cell-based Merchant-Nemhauser model for the system optimum dynamic traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 329-342, February.
    4. Lu, Gongyuan & Nie, Yu(Marco) & Liu, Xiaobo & Li, Denghui, 2019. "Trajectory-based traffic management inside an autonomous vehicle zone," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 76-98.
    5. Chen, Huey-Kuo & Hsueh, Che-Fu, 1998. "A model and an algorithm for the dynamic user-optimal route choice problem," Transportation Research Part B: Methodological, Elsevier, vol. 32(3), pages 219-234, April.
    6. Long, Jiancheng & Szeto, W.Y. & Huang, Hai-Jun & Gao, Ziyou, 2015. "An intersection-movement-based stochastic dynamic user optimal route choice model for assessing network performance," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 182-217.
    7. Ran, Bin & Boyce, David E., 1995. "Ideal Dynamic User-Optimal Route Choice: A Link-Based Variational Inequality Formulation," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3t4686x6, Institute of Transportation Studies, UC Berkeley.
    8. Han, Ke & Friesz, Terry L. & Yao, Tao, 2013. "A partial differential equation formulation of Vickrey’s bottleneck model, part II: Numerical analysis and computation," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 75-93.
    9. Zhu, Feng & Ukkusuri, Satish V., 2017. "Efficient and fair system states in dynamic transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 272-289.
    10. Sheu, Jiuh-Biing, 2006. "A composite traffic flow modeling approach for incident-responsive network traffic assignment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 461-478.
    11. Lam, William H. K. & Huang, Hai-Jun, 1995. "Dynamic user optimal traffic assignment model for many to one travel demand," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 243-259, August.
    12. Long, Jiancheng & Szeto, W.Y. & Du, Jie & Wong, R.C.P., 2017. "A dynamic taxi traffic assignment model: A two-level continuum transportation system approach," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 222-254.
    13. Long, Jiancheng & Szeto, W.Y. & Gao, Ziyou & Huang, Hai-Jun & Shi, Qin, 2016. "The nonlinear equation system approach to solving dynamic user optimal simultaneous route and departure time choice problems," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 179-206.
    14. Li, Jun & Fujiwara, Okitsugu & Kawakami, Shogo, 2000. "A reactive dynamic user equilibrium model in network with queues," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 605-624, November.
    15. Carey, Malachy & Watling, David, 2012. "Dynamic traffic assignment approximating the kinematic wave model: System optimum, marginal costs, externalities and tolls," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 634-648.
    16. Byung-Wook Wie, 1995. "A differential game approach to the dynamic mixed behavior traffic network equilibrium problem," European Journal of Operational Research, Elsevier, vol. 83(1), pages 117-136, May.
    17. Zhang, Pinchao & Qian, Sean, 2020. "Path-based system optimal dynamic traffic assignment: A subgradient approach," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 41-63.
    18. Friesz, Terry L. & Kim, Taeil & Kwon, Changhyun & Rigdon, Matthew A., 2011. "Approximate network loading and dual-time-scale dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 176-207, January.
    19. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    20. Li, Xue-yan & Li, Xue-mei & Yang, Lingrun & Li, Jing, 2018. "Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 77-92.

    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:29:y:1995:i:3:p:155-170. 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.