IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/165086.html
   My bibliography  Save this article

Dynamic Analysis of Traffic State and Congestion Propagation on Bidirectional Grid Network

Author

Listed:
  • Shu-bin Li
  • Bai-bai Fu
  • Jian-feng Zheng

Abstract

Many traffic problems in China such as traffic jams and air pollutions are mainly caused by the increasing traffic volume. In order to alleviate the traffic congestion and improve the network performance, the analysis of traffic state and congestion propagation has attracted a great interest. In this paper, an improved mesoscopic traffic flow model is proposed to capture the speed-density relationship on segments, the length of queue, the flow on links, and so forth, The self-developed dynamic traffic simulation software (DynaCHINA) is used to reproduce the traffic congestion and propagation in a bidirectional grid network for different demand levels. The simulation results show that the proposed model and method are capable of capturing the real traffic states. Hence, our results can provide decision supports for the urban traffic management and planning.

Suggested Citation

  • Shu-bin Li & Bai-bai Fu & Jian-feng Zheng, 2013. "Dynamic Analysis of Traffic State and Congestion Propagation on Bidirectional Grid Network," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-7, November.
    • Handle: RePEc:hin:jnddns:165086
    DOI: 10.1155/2013/165086
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/DDNS/2013/165086.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/DDNS/2013/165086.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2013/165086?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
    ---><---

    References listed on IDEAS

    as
    1. Ziyou, Gao & Yifan, Song, 2002. "A reserve capacity model of optimal signal control with user-equilibrium route choice," Transportation Research Part B: Methodological, Elsevier, vol. 36(4), pages 313-323, May.
    2. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part III: Multi-destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 305-313, August.
    3. Daganzo, Carlos F. & Laval, Jorge A., 2005. "Moving bottlenecks: A numerical method that converges in flows," Transportation Research Part B: Methodological, Elsevier, vol. 39(9), pages 855-863, November.
    4. Wright, Chris & Roberg, Penina, 1998. "The conceptual structure of traffic jams," Transport Policy, Elsevier, vol. 5(1), pages 23-35, January.
    5. Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2007. "Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1114-1138, December.
    6. Roberg, Penina & Abbess, Christopher R., 1998. "Diagnosis and treatment of congestion in central urban areas," European Journal of Operational Research, Elsevier, vol. 104(1), pages 218-230, January.
    7. Lam, William H. K. & Yin, Yafeng, 2001. "An activity-based time-dependent traffic assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 35(6), pages 549-574, July.
    8. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 281-287, August.
    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. Guo, Yajuan & Yang, Licai & Hao, Shenxue & Gao, Jun, 2019. "Dynamic identification of urban traffic congestion warning communities in heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 98-111.

    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. Jiancheng Long & Ziyou Gao & Xiaomei Zhao & Aiping Lian & Penina Orenstein, 2011. "Urban Traffic Jam Simulation Based on the Cell Transmission Model," Networks and Spatial Economics, Springer, vol. 11(1), pages 43-64, March.
    2. Ngoduy, D. & Hoang, N.H. & Vu, H.L. & Watling, D., 2016. "Optimal queue placement in dynamic system optimum solutions for single origin-destination traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 148-169.
    3. He, Yifan & Zeng, An, 2024. "Expanding bottlenecks reveals hidden bottlenecks and leads to more congested city centers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    4. Tampère, Chris M.J. & Corthout, Ruben & Cattrysse, Dirk & Immers, Lambertus H., 2011. "A generic class of first order node models for dynamic macroscopic simulation of traffic flows," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 289-309, January.
    5. Jin, Wen-Long, 2015. "Continuous formulations and analytical properties of the link transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 88-103.
    6. Simoni, Michele D. & Claudel, Christian G., 2017. "A fast simulation algorithm for multiple moving bottlenecks and applications in urban freight traffic management," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 238-255.
    7. Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2007. "Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1114-1138, December.
    8. Seo, Toru & Kawasaki, Yutaka & Kusakabe, Takahiko & Asakura, Yasuo, 2019. "Fundamental diagram estimation by using trajectories of probe vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 40-56.
    9. Jiang, Jiwan & Zhou, Yang & Wang, Xin & Ahn, Soyoung, 2024. "On dynamic fundamental diagrams: Implications for automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 189(C).
    10. Coifman, Benjamin A. & Mallika, Ramachandran, 2007. "Distributed surveillance on freeways emphasizing incident detection and verification," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(8), pages 750-767, October.
    11. Huanping Li & Jian Wang & Guopeng Bai & Xiaowei Hu, 2021. "Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads," Energies, MDPI, vol. 14(12), pages 1-21, June.
    12. Wang, Hongping & Fang, Yi-Ping & Zio, Enrico, 2022. "Resilience-oriented optimal post-disruption reconfiguration for coupled traffic-power systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    13. Daganzo, Carlos F., 1995. "The cell transmission model, part II: Network traffic," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 79-93, April.
    14. Ma, Tao & Zhou, Zhou & Antoniou, Constantinos, 2018. "Dynamic factor model for network traffic state forecast," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 281-317.
    15. Jin, Wen-Long, 2010. "Continuous kinematic wave models of merging traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1084-1103, September.
    16. Daganzo, Carlos F., 2006. "In traffic flow, cellular automata = kinematic waves," Transportation Research Part B: Methodological, Elsevier, vol. 40(5), pages 396-403, June.
    17. Pedro Cesar Lopes Gerum & Andrew Reed Benton & Melike Baykal-Gürsoy, 2019. "Traffic density on corridors subject to incidents: models for long-term congestion management," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 795-831, December.
    18. Jin, Wen-Long, 2018. "Unifiable multi-commodity kinematic wave model," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 639-659.
    19. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "A stochastic dynamic network loading model for mixed traffic with autonomous and human-driven vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    20. Armbruster, D. & de Beer, C. & Freitag, M. & Jagalski, T. & Ringhofer, C., 2006. "Autonomous control of production networks using a pheromone approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 104-114.

    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:hin:jnddns:165086. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.