IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v29y1995i6p407-431.html
   My bibliography  Save this article

A phenomenological model for dynamic traffic flow in networks

Author

Listed:
  • Hilliges, Martin
  • Weidlich, Wolfgang

Abstract

A macroscopic model for dynamic traffic flow is presented. The main goal of the model is the real time simulation of large freeway networks with multiple sources and sinks. First, we introduce the model in its discrete formulation and consider some of its properties. It turns out, that our non-hydrodynamical ansatz for the flows results in a very advantageous behavior of the model. Next the fitting conditions at junctions of a traffic network are discussed. In the following sections we carry out a continuous approximation of our discrete model in order to derive stationary solutions and to consider the stability of the homogeneous one. It turns out, that for certain conditions unstable traffic flow occurs. In a subsequent section, we compare the stability of the discrete model and the corresponding continuous approximation. This confirms in retrospection the close similarities of both model versions. Finally we compare the results of our model with the results of another macroscopic model, that was recently suggested by Kerner and Konhäuser [Phys. Rev. E 48, 2335-2338 (1993)].

Suggested Citation

  • Hilliges, Martin & Weidlich, Wolfgang, 1995. "A phenomenological model for dynamic traffic flow in networks," Transportation Research Part B: Methodological, Elsevier, vol. 29(6), pages 407-431, December.
  • Handle: RePEc:eee:transb:v:29:y:1995:i:6:p:407-431
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0191-2615(95)00018-9
    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. Denos C. Gazis & Robert Herman & Richard W. Rothery, 1961. "Nonlinear Follow-the-Leader Models of Traffic Flow," Operations Research, INFORMS, vol. 9(4), pages 545-567, August.
    2. Ross, Paul, 1988. "Traffic dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 22(6), pages 421-435, December.
    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. Helbing, Dirk, 1995. "Theoretical foundation of macroscopic traffic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 219(3), pages 375-390.
    2. Osorio, Carolina & Flötteröd, Gunnar & Bierlaire, Michel, 2011. "Dynamic network loading: A stochastic differentiable model that derives link state distributions," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1410-1423.
    3. Helbing, Dirk, 1997. "Modeling multi-lane traffic flow with queuing effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 242(1), pages 175-194.
    4. Boel, René & Mihaylova, Lyudmila, 2006. "A compositional stochastic model for real time freeway traffic simulation," Transportation Research Part B: Methodological, Elsevier, vol. 40(4), pages 319-334, May.
    5. Helbing, Dirk & Hennecke, Ansgar & Shvetsov, Vladimir & Treiber, Martin, 2001. "MASTER: macroscopic traffic simulation based on a gas-kinetic, non-local traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 35(2), pages 183-211, February.

    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. Zheng, Liang & Jin, Peter J. & Huang, Helai, 2015. "An anisotropic continuum model considering bi-directional information impact," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 36-57.
    2. Zhang, H. M., 1998. "A theory of nonequilibrium traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 485-498, September.
    3. Jiang, Rui & Wu, Qing-Song & Zhu, Zuo-Jin, 2002. "A new continuum model for traffic flow and numerical tests," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 405-419, June.
    4. Jiang, Rui & Wu, Qing-Song, 2003. "Study on propagation speed of small disturbance from a car-following approach," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 85-99, January.
    5. Jin, Wen-Long, 2016. "On the equivalence between continuum and car-following models of traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 543-559.
    6. Nakata, Makoto & Yamauchi, Atsuo & Tanimoto, Jun & Hagishima, Aya, 2010. "Dilemma game structure hidden in traffic flow at a bottleneck due to a 2 into 1 lane junction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(23), pages 5353-5361.
    7. McCrea, Jennifer & Moutari, Salissou, 2010. "A hybrid macroscopic-based model for traffic flow in road networks," European Journal of Operational Research, Elsevier, vol. 207(2), pages 676-684, December.
    8. Li, Xiaopeng & Wang, Xin & Ouyang, Yanfeng, 2012. "Prediction and field validation of traffic oscillation propagation under nonlinear car-following laws," Transportation Research Part B: Methodological, Elsevier, vol. 46(3), pages 409-423.
    9. Wang, Xiao & Jiang, Rui & Li, Li & Lin, Yi-Lun & Wang, Fei-Yue, 2019. "Long memory is important: A test study on deep-learning based car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 786-795.
    10. Coifman, Benjamin & Ponnu, Balaji, 2020. "Adjacent lane dependencies modulating wave velocity on congested freeways-An empirical study," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 84-99.
    11. Chandle Chae & Youngho Kim, 2023. "Investigation of Following Vehicles’ Driving Patterns Using Spectral Analysis Techniques," Sustainability, MDPI, vol. 15(13), pages 1-15, July.
    12. Zhang, H.M. & Kim, T., 2005. "A car-following theory for multiphase vehicular traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 39(5), pages 385-399, June.
    13. Georgia Perakis & Guillaume Roels, 2006. "An Analytical Model for Traffic Delays and the Dynamic User Equilibrium Problem," Operations Research, INFORMS, vol. 54(6), pages 1151-1171, December.
    14. Rehborn, Hubert & Klenov, Sergey L. & Palmer, Jochen, 2011. "An empirical study of common traffic congestion features based on traffic data measured in the USA, the UK, and Germany," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4466-4485.
    15. Kaur, Ramanpreet & Sharma, Sapna, 2018. "Modeling and simulation of driver’s anticipation effect in a two lane system on curved road with slope," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 110-120.
    16. Nelson, Paul & Sopasakis, Alexandros, 1998. "The prigogine-herman kinetic model predicts widely scattered traffic flow data at high concentrations," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 589-604, November.
    17. Yifan Pan & Yongjiang Wang & Baobin Miao & Rongjun Cheng, 2022. "Stabilization Strategy of a Novel Car-Following Model with Time Delay and Memory Effect of the Driver," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    18. Xiangyang Cao & Bingzhong Zhou & Qiang Tang & Jiaqi Li & Donghui Shi, 2018. "Urban Wasteful Transport and Its Estimation Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    19. Hongxing Zhao & Ruichun He & Xiaoyan Jia, 2019. "Estimation and Analysis of Vehicle Exhaust Emissions at Signalized Intersections Using a Car-Following Model," Sustainability, MDPI, vol. 11(14), pages 1-25, July.
    20. Kai Nagel & Peter Wagner & Richard Woesler, 2003. "Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling," Operations Research, INFORMS, vol. 51(5), pages 681-710, October.

    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:6:p:407-431. 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.