Skip to main content
SpringerLink
Log in

Maximum Green Time Settings for Traffic-Actuated Signal Control at Isolated Intersections Using Fuzzy Logic

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

Traffic-actuated control (TAC) is widely used for signal control in isolated intersections. In TAC, green durations are dynamically determined based on online traffic data. These determinations are subject to predefined static parameters which do not respond to sudden changes in traffic flow. One type of these parameters in TAC is maximum green time. In this paper, maximum green times are dynamically determined by means of fuzzy control. At first, it monitors the whole intersection traffic conditions and then dynamically adjusts maximum green times. The main advantage of the proposed approach is its capability to adjust maximum green times which are responsive to real-time traffic condition in isolated intersections. The efficiency of the proposed method has been evaluated by AIMSUN 7 microscopic traffic simulation tool. The evaluation results show the efficiency and the robustness of the proposed method compared to maximum green times provided by SYNCHRO8 and state-of-the-art dynamic stochastic approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Yin, Y.: Robust optimal traffic signal timing. Transp. Res. Part B 42, 911–924 (2008)

    Article  Google Scholar 

  2. Hunt, P.B., Winton, R.I., Robertson, D.I., Bretherton, R.D.: SCOOT—a traffic responsive method of coordinating signals, Transport and Road Research Laboratory (1981)

  3. Sims, A.G., Dobinson, K.W.: The Sydney coordinated adaptive traffic (Scat) system philosophy and benefits. Veh. Technol. IEEE Trans. 29, 130–137 (1980)

  4. Mirchandani, P., Fei-Yue, W.: RHODES to intelligent transportation systems. Intell. Syst. IEEE 20, 10–15 (2005)

    Article  Google Scholar 

  5. Gartner N. H.: OPAC: a demand-responsive strategy for traffic signal control, In: Transportation Research Record., vol. 906, (1983)

  6. Kronborg, F.D.P.: MOVA AND LOHVRA: traffic signal control for isolated intersections. Traffic Eng. Control 34, 195–200 (1993)

    Google Scholar 

  7. Smith, B.L., Scherer, W.T., Hauser, T.A., Park, B.B.: Data-driven methodology for signal timing plan development: a computational approach. Computer-Aided Civ. Infrastruct. Eng. 17, 387–395 (2002)

    Article  Google Scholar 

  8. Kim, J.T., Courage, K.G.: Evaluation and design of maximum green time settings for traffic actuated control. Transp. Res. Rec 1852, 246–255 (2003)

    Article  Google Scholar 

  9. Kell, J. H., Fullerton, I. J.: Manual of Traffic Signal Design, 2nd Edn. Institute of Transportation Engineers, Washington, D.C. (1998)

  10. Lin, F.B.: Estimating average cycle lengths and green intervals of semi-actuated signal operations for level of service analysis. Transp. Res. Rec. 1287, 119–128 (1990)

    Google Scholar 

  11. Orcutt, FL.: The traffic signal book. Prentice-Hall, Englewood Cliffs, NJ (1993)

  12. Courage, G., Luh, J. Z., Wallace, C. E., Development of guidelines for implementing computerized timing designs at traffic actuated signals. Gainesville, FL: Transport Research Center, 1989

  13. Yun, I., Best, M., Park, B.: Evaluation of adaptive maximum feature in actuated traffic controller: hardware-in-the-loop simulation. Transp. Res. Rec. 2035, 134–140 (2007)

    Article  Google Scholar 

  14. Guohui, Z., Yinhai, W.: Optimizing minimum and maximum green time settings for traffic actuated control at isolated intersections. Intell. Transp. Syst. IEEE Trans. 12, 164–173 (2011)

    Article  Google Scholar 

  15. Pappis, C.P., Mamdani, E.H.: A fuzzy logic controller for a traffic junction. Syst. Man Cybern IEEE Trans. 7, 707–717 (1977)

    Article  MATH  Google Scholar 

  16. Niittymaki, J., Kikuchi, S.: Application of fuzzy logic to the control of a pedestrian crossing signal. Transp. Res. Rec. 1651, 30–38 (1998)

    Article  Google Scholar 

  17. Trabia, M.B., Kaseko, M.S., Ande, M.: A two-stage fuzzy logic controller for traffic signals. Transp. Res. Part C 7, 353–367 (1999)

    Article  Google Scholar 

  18. Murat, Y.S., Gedizlioglu, E.: A fuzzy logic multi-phased signal control model for isolated junctions. Transp. Res. Part C 13, 19–36 (2005)

    Article  Google Scholar 

  19. Schmöcker, J.-D., Ahuja, S., Bell, M.G.H.: Multi-objective signal control of urban junctions—Framework and a London case study. Transp. Res. Part C 16, 454–470 (2008)

    Article  Google Scholar 

  20. Chiu S., Chand, S.: Adaptive traffic signal control using fuzzy logic. In: Fuzzy Systems, 1993, Second IEEE International Conference on, 1993, vol. 2, pp. 1371–1376 (1993)

  21. Tsin Hing, H., Tin-Kin, H., Yu-Fai, F.: Coordinated road-junction traffic control by dynamic programming. In: Intelligent Transportation Systems. IEEE Transactions on, vol. 6, pp. 341–350. (2005)

  22. Zaied, A.N.H., Al Othman, W.: Development of a fuzzy logic traffic system for isolated signalized intersections in the State of Kuwait. Expert Syst. Appl. 38, 9434–9441 (2011)

    Article  Google Scholar 

  23. Borkar, P., Sarode, M.V., Malik, L.G.: Modality of Adaptive neuro-fuzzy classifier for acoustic signal-based traffic density state estimation employing linguistic hedges for feature selection. Int. J. Fuzzy Syst. 3, 1–16 (2015)

    Google Scholar 

  24. Head, L., Gettman, D., Wei, Z.: decision model for priority control of traffic signals. Transp. Res. Rec. 1978, 169–177 (2006)

    Article  Google Scholar 

  25. Association, N.E.M., National Transportation Communicatio Definitions for ITS Protocol: Object for Actuated Traffic Signal Controller (ASC) Units 1202 v01.07, January 2005

  26. Zanin, M., Messelodi, S., Modena, C. M.: An efficient vehicle queue detection system based on image processing, In: Image Analysis and Processing, 2003. Proceedings. 12th International Conference on, 2003, pp. 232–237, (2003)

  27. Zheng, J., Wang, Y., Nihan, N.L., Hallenbeck, M.E.: Detecting cycle failures at signalized intersections using video image processing. Computer-Aided Civ. Infrastruct. Eng. 21, 425–435 (2006)

    Article  Google Scholar 

  28. Satzoda, R. K., Suchitra, S., Srikanthan, T., Chia, J. Y.: Vision-based vehicle queue detection at traffic junctions, In: Industrial Electronics and Applications (ICIEA), 2012 7th IEEE Conference on, 2012, pp. 90–95, (2012)

  29. Highway Capacity Manual, Transportation Research Board of the National Academies, Washington, D.C. (2010)

  30. Barcelo, J.: Fundamentals of Traffic Simulations, vol. 145. Springer, New York (2010)

    Book  Google Scholar 

  31. Koonce, P., Rodegerdts, L., Lee, K., Urbanik, T.: Traffic signal timing manual. Federal Highway Administration, Kittelson & Associates, Inc. (2008)

  32. TSS., Aimsun 7 Dynamic Simulators Users Manual v7, Transport Simulation Systems, Barcelona, Spain (2012)

  33. Trafficware, Synchro Studio 8 User Guide, Trafficware, SugarLand, TX (2011)

  34. Arslan, A., Kaya, M.: Determination of fuzzy logic membership functions using genetic algorithms. Fuzzy Sets Syst. 118, 297–306 (2001)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Mathematics, Shiraz University of Technology, Shiraz, Iran

    M. J. Shirvani Shiri & H. R. Maleki

Authors
  1. M. J. Shirvani Shiri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. R. Maleki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to H. R. Maleki.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shirvani Shiri, M.J., Maleki, H.R. Maximum Green Time Settings for Traffic-Actuated Signal Control at Isolated Intersections Using Fuzzy Logic. Int. J. Fuzzy Syst. 19, 247–256 (2017). https://doi.org/10.1007/s40815-016-0143-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-016-0143-7

Keywords

Search

Navigation