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A Traffic Breakdown Model Based on Queueing Theory

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  • 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
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    References listed on IDEAS

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    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
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    2. 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.
    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. 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.

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