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Optimization of traffic signal parameters based on distribution of link travel time

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Abstract

In order to make full use of digital data, such as data extracted from electronic police video systems, and optimize intersection signal parameters, the theoretical distribution of the vehicle’s road travel time must first be determined. The intersection signal cycle and the green splits were optimized simultaneously, and the system total travel time was selected as the optimization goal. The distribution of the vehicle’s link travel time is the combined results of the flow composition, road marking, the form of control, and the driver’s driving habits. The method proposed has 15% lower system total stop delay and fewer total stops than the method of TRRL (Transport and Road Research Laboratory) in England and the method of ARRB (Australian Road Research Board) in Australia. This method can save 0.5% total travel time and will be easier to understand and test, which establishes a causal relationship between optimal results and specific forms of road segment management, such as speed limits.

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References

  1. Transportation Research Board. Signal timing practices and procedures-state of the practice [R]. Washington, DC: National Research Council, 2005.

    Google Scholar 

  2. WEBSTER F V. Traffic signal settings. Road research technical paper, No.39 [R]. London: Great Britain Road Research Laboratory, 1958.

    Google Scholar 

  3. SUN Wei-li, WU Xin-kai, WANG Yun-peng, YU Gui-zhen. A continuous-flow-intersection-lite design and traffic control for oversaturated bottleneck intersections [J]. Transportation Research Part C, 2015, 56: 18–33.

    Article  Google Scholar 

  4. AKCELIK R. Traffic signals: Capacity and timing analysis. ARRB Research Record No. 123 [R]. Australia: ARRB Transport Research Ltd, 1998.

    Google Scholar 

  5. Transportation Research Board. Highway capacity manual 2000 [R]. Washington, DC: National Research Council, 2000.

    Google Scholar 

  6. CHANG T H, LIN J T. Optimal signal timing for an oversaturated intersection [J]. Transportation Research Part B, 2000, 34(6): 471–491.

    Article  Google Scholar 

  7. PAIK B. Enhanced genetic algorithm for signal timing optimization of oversaturated intersections [J]. Transportation Research Record 1 727, National Research Council Washington, D. C. 2000: 32–41.

    Google Scholar 

  8. PAPPIS C P, MAMDAM E H. A fuzzy logic controller for a traffic junction [J]. IEEE Transactions on Systems, Man and Cybernetics, 1977, 1(10): 707–717.

    Article  MATH  Google Scholar 

  9. TRABIA M B, KASEKO M S, ANDO M. A two-stage fuzzy logic controller for traffic signals [J]. Transportation Research Part C, 1999, 7(6): 353–367.

    Article  Google Scholar 

  10. TAKASHI N, TERUTOSHI K. Development of a self-organizing traffic control system using neural network models [J]. Transportation Research Record, 1991: 137–145.

    Google Scholar 

  11. FOY M D, BENEKOHAL R F, GOLDBERG D E. Signal timing determination using genetic algorithms [J]. Transportation Research Record, 1992: 108–115.

    Google Scholar 

  12. CEYLAN H, BELL M G H. Traffic signal timing optimization based on genetic algorithm approach, including drivers’ routing [J]. Transportation Research Part B, 2004, 38(4): 329–342.

    Article  Google Scholar 

  13. HE J J, HOU Z E. Ant colony algorithm for traffic signal timing optimization [J]. Advances in Engineering Software, 2012, 43(1): 14–18.

    Article  MATH  Google Scholar 

  14. MITSURU S, ZHONG F J. Artificial neural network–based heuristic optimal traffic signal timing [J]. Computer-aided Civil and Infrastructure Engineering, 2000, 15(4): 293–307.

    Google Scholar 

  15. LI Mao-sheng, XU Hong-li, SHI Feng. Analytic method for determining traffic signal impact on vehicle journey time distribution [C] // International Workshop on Computational Transportation Science, Wuhan, China: IWCTS, 2016.

    Google Scholar 

  16. LI Mao-sheng, LIU Zheng-qiu, ZHANG Yong-hong, LIU Wei-jun, SHI Feng. Distribution analysis of train interval journey time employing the censored model with shifting character [J]. Journal of Applied Statistics, 2016. DOI: 10.1080/02664763. 2016.1182134.

    Google Scholar 

  17. LO H K, LUO X W, SIU B W Y. Degradable transport network: Travel time budget of travelers with heterogeneous risk aversion [J]. Transportation Research Part B, 2006, 40(9): 792–806.

    Article  Google Scholar 

  18. CHEN A, ZHOU Z. The a-reliable mean-excess traffic equilibrium model with stochastic travel times [J]. Transportation Research Part B, 2010, 44(4): 493–513.

    Article  MathSciNet  Google Scholar 

  19. DAVID K H, BYUNGKYU B P, ALEKSANDAR S, SU Peng, MA Jia-qi. Optimality versus run time for isolated signalized intersections [J]. Transportation Research Part C, 2015, 55: 191–202.

    Article  Google Scholar 

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Correspondence to Mao-sheng Li  (黎茂盛).

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Foundation item: Project(14BTJ017) supported by National Social Science Foundation Project of China; Project supported by the 2014 Mathematics and Interdisciplinary Science Project of Central South University, China

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Li, Ms., Xue, Hl. & Shi, F. Optimization of traffic signal parameters based on distribution of link travel time. J. Cent. South Univ. 24, 432–441 (2017). https://doi.org/10.1007/s11771-017-3445-5

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  • DOI: https://doi.org/10.1007/s11771-017-3445-5

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