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Traffic jam in signalized road network

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Abstract

Traffic jam in large signalized road network presents a complex nature. In order to reveal the jam characteristics, two indexes, SVS (speed of virtual signal) and VOS (velocity of spillover), were proposed respectively. SVS described the propagation of queue within a link while VOS reflected the spillover velocity of vehicle queue. Based on the two indexes, network jam simulation was carried out on a regular signalized road network. The simulation results show that: 1) The propagation of traffic congestion on a signalized road network can be classified into two stages: virtual split driven stage and flow rate driven stage. The former stage is characterized by decreasing virtual split while the latter only depends on flow rate; 2) The jam propagation rate and direction are dependent on traffic demand distribution and other network parameters. The direction with higher demand gets more chance to be jammed. Our findings can serve as the basis of the prevention of the formation and propagation of network traffic jam.

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References

  1. [1]

    LIU Tian-liang, HUANG Hai-jun, TIAN Li-jun. Microscopic simulation of multi-lane traffic under dynamic tolling and information feedback [J]. Journal of Central South University of Technology, 2009, 16(5): 865–870.

  2. [2]

    TANG Tie-qiao, LI Chuan-yao, HUANG Wai-jun, SHANG Hua-yan. Macro modeling and analysis of traffic flow with road width [J]. Journal of Central South University of Technology, 2011, 18(5): 1757–1764.

  3. [3]

    BIHAM O, A. Alan Middleton, Dov Levine. Self-organization and a dynamical transition in traffic-flow models [J]. Phys. Rev. A, 1992, 46(10): 6124–6127.

  4. [4]

    CHUNG K H, HUI P M. Two-dimensional traffic flow problems with faulty traffic lights [J]. Phys Rev E, 1995, 51(1): 772–774.

  5. [5]

    NAGATANI T. Effect of jam-avoiding turn on jamming transition in two-dimensional traffic flow model [J]. Journal of the Physical Society of Japan, 1994, 63(4): 1228–1231.

  6. [6]

    ZHAO Xiao-mei, XIE Dong-fan, JIA Bin, JIANG Rui, GAO Zi-you. Disorder structure of free-flow and global jams in the extended BML model [J]. Physics Letters A, 2011, 375(7): 1142–1147.

  7. [7]

    WRIGHT C, ROBERG P. The conceptual structure of traffic jams [J]. Transp Policy, 1998, 5: 23–35.

  8. [8]

    ROBERG-ORENSTEIN P. The development and control of traffic jams acused by incidents in rectangular networks [D]. Middlesex: Middlesex University, 1997: 76–80

  9. [9]

    ROBERG P, CHRISTOPHER R A. Diagnosis and treatment of congestion in central urban areas [J]. European Journal of Operational Research, 1998, 104(1): 218–230.

  10. [10]

    ROBERG-ORENSTEIN P, ABBESS C, WRIGHT C. Traffic jam simulation [J]. Journal of Maps, 2007 (2): 107–121.

  11. [11]

    JIANG Xian-cai, PEI Yu-long. Delay model of adaptive signal control using fixed number theory [J]. Journal of Transportation Systems Engineering and Information Technology, 2008, 8(3): 66–70.

  12. [12]

    DAGANZO-CARLOS F. The cell transmission model, part II-Network traffic [J]. Transportation Research Part B, 1995, 29B(2): 79–93.

  13. [13]

    DAGANZO CARLOS F. Urban gridlock: Macroscopic modeling and mitigation approaches [J]. Transportation Research Part B: Methodological, 2007, 41(1): 49–62.

  14. [14]

    WANG Ping, JONES L S, Qun Yang. A novel conditional cell transmission model for oversaturated arterials [J]. Journal of Central South University, 2012, 19(5): 1466–1474.

  15. [15]

    SHEFFI YOSEF. Urban transportation networks: equilibrium analysis with mathematical programming methods [M]. Englewood Cliffs, NJ 07632: Prentice-Hall, Inc., 1985

  16. [16]

    WEBSTER F V, COBBE B M. Traffic signals [J]. London. U.K: Road Research Laboratory, HMSO, 1966.

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Author information

Correspondence to Dian-hai Wang 王殿海.

Additional information

Foundation item: Project(2012CB725402) supported by the State Key Development Program for Basic Research of China; Project(2012MS21175) supported by the National Science Foundation for Post-doctoral Scientists of China; Project(Bsh1202056) supported by the Excellent Postdoctoral Science Foundation of Zhejiang Province, China

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Qi, H., Wang, D., Chen, P. et al. Traffic jam in signalized road network. J. Cent. South Univ. 21, 832–842 (2014). https://doi.org/10.1007/s11771-014-2007-3

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Key words

  • traffic engineering
  • network traffic jam
  • virtual signal
  • traffic control