IDEAS home Printed from https://ideas.repec.org/a/kap/netspa/v14y2014i3p485-504.html
   My bibliography  Save this article

A Traffic Breakdown Model Based on Queueing Theory

Author

Listed:
  • Xiqun (Michael) Chen
  • Zhiheng Li
  • Li Li
  • Qixin Shi

Abstract

In this paper, we propose a queueing model to describe traffic breakdown phenomena caused by perturbations of on-ramp merging vehicles. In congested mainline traffic flow, we assume that a merging vehicle will trigger a jam queue formulation. If this jam queue cannot dissipate before the next vehicle merges into the main road, it could grow into a wide jam and eventually result in traffic breakdown. Different from many existing models that focused on the propagation of jam waves, the proposed model emphasizes the size evolution of a jam queue (local congested vehicle cluster) instead of its spatial evolutions. This new approach reduces analysis difficulties and allows us to directly link microscopic driving behaviors with macroscopic breakdown phenomena. Test results show that the simulated breakdown probability curve (parameter tuning using Next Generation Simulation vehicular trajectories) fits with the empirical breakdown probability curve that is estimated by Performance Measurement System (PeMS) data. This indicates that this new model can account for the probability of breakdown phenomena and help us set an appropriate inflow rate so as to void breakdown and meanwhile maintain a high road capacity. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Xiqun (Michael) Chen & Zhiheng Li & Li Li & Qixin Shi, 2014. "A Traffic Breakdown Model Based on Queueing Theory," Networks and Spatial Economics, Springer, vol. 14(3), pages 485-504, December.
    • Handle: RePEc:kap:netspa:v:14:y:2014:i:3:p:485-504
    DOI: 10.1007/s11067-014-9246-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11067-014-9246-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11067-014-9246-6?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
    ---><---

    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. Zhang, Lei & Levinson, David, 2010. "Ramp metering and freeway bottleneck capacity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 218-235, May.
    2. Coifman, Benjamin & Kim, Seoungbum, 2011. "Extended bottlenecks, the fundamental relationship, and capacity drop on freeways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 980-991, November.
    3. Ahn, Soyoung & Cassidy, Michael J. & Laval, Jorge, 2004. "Verification of a simplified car-following theory," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 431-440, June.
    4. Hwasoo Yeo & Alexander Skabardonis, 2009. "Understanding Stop-and-go Traffic in View of Asymmetric Traffic Theory," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 99-115, Springer.
    5. Kim, T. & Zhang, H.M., 2008. "A stochastic wave propagation model," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 619-634, August.
    6. Chiabaut, Nicolas & Leclercq, Ludovic & Buisson, Christine, 2010. "From heterogeneous drivers to macroscopic patterns in congestion," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 299-308, February.
    7. D. Helbing & M. Treiber & A. Kesting & M. Schönhof, 2009. "Theoretical vs. empirical classification and prediction of congested traffic states," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 69(4), pages 583-598, June.
    8. Kerner, Boris S. & Klenov, Sergey L., 2006. "Probabilistic breakdown phenomenon at on-ramp bottlenecks in three-phase traffic theory: Congestion nucleation in spatially non-homogeneous traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 473-492.
    9. Laval, Jorge A., 2011. "Hysteresis in traffic flow revisited: An improved measurement method," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 385-391, February.
    10. Newell, G. F., 2002. "A simplified car-following theory: a lower order model," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 195-205, March.
    11. Justin Geistefeldt & Werner Brilon, 2009. "A Comparative Assessment of Stochastic Capacity Estimation Methods," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 583-602, Springer.
    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. Fiems, Dieter & Prabhu, Balakrishna & De Turck, Koen, 2019. "Travel times, rational queueing and the macroscopic fundamental diagram of traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 412-421.
    2. Han, Youngjun & Ahn, Soyoung, 2018. "Stochastic modeling of breakdown at freeway merge bottleneck and traffic control method using connected automated vehicle," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 146-166.
    3. Petter Arnesen & Odd A. Hjelkrem, 2018. "An Estimator for Traffic Breakdown Probability Based on Classification of Transitional Breakdown Events," Transportation Science, INFORMS, vol. 52(3), pages 593-602, June.
    4. Wei, Yuguang & Avcı, Cafer & Liu, Jiangtao & Belezamo, Baloka & Aydın, Nizamettin & Li, Pengfei(Taylor) & Zhou, Xuesong, 2017. "Dynamic programming-based multi-vehicle longitudinal trajectory optimization with simplified car following models," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 102-129.

    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. Laval, Jorge A. & Toth, Christopher S. & Zhou, Yi, 2014. "A parsimonious model for the formation of oscillations in car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 228-238.
    2. Blandin, Sébastien & Argote, Juan & Bayen, Alexandre M. & Work, Daniel B., 2013. "Phase transition model of non-stationary traffic flow: Definition, properties and solution method," Transportation Research Part B: Methodological, Elsevier, vol. 52(C), pages 31-55.
    3. Han, Youngjun & Ahn, Soyoung, 2018. "Stochastic modeling of breakdown at freeway merge bottleneck and traffic control method using connected automated vehicle," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 146-166.
    4. Jabari, Saif Eddin & Zheng, Jianfeng & Liu, Henry X., 2014. "A probabilistic stationary speed–density relation based on Newell’s simplified car-following model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 205-223.
    5. 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.
    6. Saif Eddin Jabari & Laura Wynter, 2016. "Sensor placement with time-to-detection guarantees," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(4), pages 415-433, December.
    7. Taylor, Jeffrey & Zhou, Xuesong & Rouphail, Nagui M. & Porter, Richard J., 2015. "Method for investigating intradriver heterogeneity using vehicle trajectory data: A Dynamic Time Warping approach," Transportation Research Part B: Methodological, Elsevier, vol. 73(C), pages 59-80.
    8. Chen, Danjue & Ahn, Soyoung & Laval, Jorge & Zheng, Zuduo, 2014. "On the periodicity of traffic oscillations and capacity drop: The role of driver characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 117-136.
    9. Sun, Jie & Zheng, Zuduo & Sun, Jian, 2020. "The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based control," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 58-83.
    10. Zheng, Zuduo & Ahn, Soyoung & Chen, Danjue & Laval, Jorge, 2011. "Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1378-1388.
    11. Qian, Wei-Liang & F. Siqueira, Adriano & F. Machado, Romuel & Lin, Kai & Grant, Ted W., 2017. "Dynamical capacity drop in a nonlinear stochastic traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 328-339.
    12. Wei, Dali & Liu, Hongchao, 2013. "Analysis of asymmetric driving behavior using a self-learning approach," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 1-14.
    13. Zhao, Jing & Knoop, Victor L. & Wang, Meng, 2020. "Two-dimensional vehicular movement modelling at intersections based on optimal control," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 1-22.
    14. 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.
    15. Jung, Jaeyoung & Chen, Rex & Jin, Wenlong & Jayakrishnan, R. & Regan, Amelia C, 2010. "An Empirical Study of Inter-Vehicle Communication Performance Using NS-2," University of California Transportation Center, Working Papers qt874253j6, University of California Transportation Center.
    16. Xu, Tu & Laval, Jorge, 2020. "Statistical inference for two-regime stochastic car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 210-228.
    17. 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.
    18. Treiber, Martin & Kesting, Arne, 2018. "The Intelligent Driver Model with stochasticity – New insights into traffic flow oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 613-623.
    19. Yao, Handong & Li, Qianwen & Li, Xiaopeng, 2020. "A study of relationships in traffic oscillation features based on field experiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 339-355.
    20. Jorge A. Laval & Bhargava R. Chilukuri, 2014. "The Distribution of Congestion on a Class of Stochastic Kinematic Wave Models," Transportation Science, INFORMS, vol. 48(2), pages 217-224, May.

    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:kap:netspa:v:14:y:2014:i:3:p:485-504. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.