International Journal of Transportation Engineering and Technology

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Intelligent Urban Traffic Flow Control: A Case Study on Fuzzy Logic Application

Received: 19 July 2017    Accepted: 04 August 2017    Published: 26 September 2017
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Abstract

This work uses concepts, tools, and methodologies associated to Operational Research and Artificial Intelligence to turn more efficient a system that controls traffic lights at a road crossing. Using Operational Research, through Linear Programming method, the intelligent traffic light operation is described as a mathematical formulation and constraints. That information is used for MacVicar-Whelam table elaboration that relates system pertinence rules through fuzzy logic techniques. It is pled, with the described development, to obtain of solid results for validation of the developed methodology, as well as its efficient control of intelligent traffic lights.

DOI 10.11648/j.ijtet.20170303.11
Published in International Journal of Transportation Engineering and Technology (Volume 3, Issue 3, September 2017)
Page(s) 25-38
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Artificial Intelligence, Decision Support Systems, Fuzzy Sets, Simulation, Urban Traffic

References
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[3] Correio do Estado, "AGETRAN instala semáforo inteligente na capital," Correio do Estado, Campo Grande, MS, 6-October-2011. [in Portuguese]
[4] G. Benjamin Júnior, "Trânsito no Grande ABC," Diário do Grande ABC, num. 1, 2004. [in Portuguese]
[5] Prefeitura Municipal de Curitiba, "Semáforos inteligentes organizam e agilizam o fluxo de veículos na cidade," Agência de Notícias, num. 2, 2005. [in Portuguese]
[6] C. E. Bognar, O. Saotome, and P. C. F. Barbosa, "Proposta de melhoria do algoritmo MCMC Gibbs Sampling para inferências Bayesianas em sistemas embarcados de tempo-real: Uma aplicação em semáforos inteligentes," in the 1st International Congress University-Industry Cooperation, Universidade de Taubaté, Ubatuba, SP, Brazil, 2005. [in Portuguese]
[7] C. E. Bognar, O. Saotome, and V. G. Ferreira, "Comparative evaluation of MCMC Gibbs Sampling and search-based algorithms for probabilistic inference in Bayesian networks," in the 1st International Congress University-Industry Cooperation, Universidade de Taubaté, Ubatuba, SP, Brazil, 2005.
[8] C. P. Pappis and E. H. Mamdani, "A fuzzy logic controller for a traffic junction," IEEE Trans. Syst. Man Cybern. – Syst., vol. 7, num. 10, pp. 707-717, 1977.
[9] C. Batur and V. Kasparian, "Model based fuzzy control," Math. Comput. Model., vol. 15, pp. 3-14, 1991.
[10] R. Bandyopadhyay and D. Patranabis, "A fuzzy logic based PI autotuner," ISA Trans., vol. 37, pp. 227-235, 1998.
[11] J. Niittymaki and M. Pursula, "Signal control using fuzzy logic," Fuzzy Sets Syst., vol. 116, pp. 11-22, 2000.
[12] R. Hoyer and U. Jumar, "An advanced fuzzy controller for traffic lights," Annu. Rev. Automat. Program., vol. 19, pp. 67-72, 1994.
[13] M. B. Trabia, M. S. Kaseko, and M. Ande, "A two-stage fuzzy logic controller for traffic signals," Transp. Res. Pt. C-Emerg. Technol., vol. 7, pp. 353-367, 1999.
[14] W.-M. Wey, "Model formulation and solution algorithm of traffic signal control in an urban network," Comput. Environ. Urban Syst., vol. 24, pp. 355-378, 2000.
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[16] J. Niittymaki and E. Turunen, "Traffic signal control on similarity logic reasoning," Fuzzy Sets Syst., vol. 133, pp. 109-131, 2003.
[17] W. Wen, "A dynamic and automatic traffic light control expert system for solving the road congestion problem," Expert Syst. Appl., vol. 34,num. 4, pp. 2370-2381, 2008.
[18] K. Aboudolas, M. Papageorgiou, and E. Kosmatopoulos, "Store-and-forward based methods for the signal control problem in large-scale congested urban road networks," Transp. Res. Pt. C-Emerg. Technol., vol. 17, pp. 163-174, 2009.
[19] S. M. Rahman and N. T. Ratrout, "Review of the fuzzy logic based approach in traffic signal control: Prospects in Saudi Arabia," J. Transport. Syst. Eng. Inf. Technol., vol. 9, pp. 58-70, 2009.
[20] C. Karakuzu and O. Demirci, "Fuzzy logic based smart traffic light simulator design and hardware implementation," Appl. Soft. Comput., vol. 10, pp. 66-73, 2010.
[21] J. García-Nieto, E. Alba, and A. C. Olivera, "Swarm intelligence for traffic light scheduling: Application to real urban areas," Eng. Appl. Artif. Intell., vol. 25, num. 2, pp. 274-283, 2012.
[22] F. Motawej, R. Bouyekhf, and A. El Moudni, "A dissipativity-based approach to traffic signal control for an over-saturated intersection," J. Frankl. Inst.-Eng. Appl. Math., vol. 348, pp. 703-717, 2011.
[23] E. L. Andrade, Introduction to Operational Research: Methods and Models for Decision Analysis, 3rd ed. Rio de Janeiro City, RJ, Brazil: Livros Técnicos e Científicos, 2004. [in Portuguese]
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Author Information
  • Department of Basic and Environmental Sciences, School of Engineering at Lorena, University of S?o Paulo, Lorena, SP, Brazil

  • Department of Mechanical Engineering, University of Taubaté, Taubaté, SP, Brazil

  • Department of Computer Science, University of Taubaté, Taubaté, SP, Brazil

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  • APA Style

    Wendell de Queiróz Lamas, Giorgio Eugenio Oscare Giacaglia, Eliana Campos de Oliveira. (2017). Intelligent Urban Traffic Flow Control: A Case Study on Fuzzy Logic Application. International Journal of Transportation Engineering and Technology, 3(3), 25-38. https://doi.org/10.11648/j.ijtet.20170303.11

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    ACS Style

    Wendell de Queiróz Lamas; Giorgio Eugenio Oscare Giacaglia; Eliana Campos de Oliveira. Intelligent Urban Traffic Flow Control: A Case Study on Fuzzy Logic Application. Int. J. Transp. Eng. Technol. 2017, 3(3), 25-38. doi: 10.11648/j.ijtet.20170303.11

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    AMA Style

    Wendell de Queiróz Lamas, Giorgio Eugenio Oscare Giacaglia, Eliana Campos de Oliveira. Intelligent Urban Traffic Flow Control: A Case Study on Fuzzy Logic Application. Int J Transp Eng Technol. 2017;3(3):25-38. doi: 10.11648/j.ijtet.20170303.11

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  • @article{10.11648/j.ijtet.20170303.11,
      author = {Wendell de Queiróz Lamas and Giorgio Eugenio Oscare Giacaglia and Eliana Campos de Oliveira},
      title = {Intelligent Urban Traffic Flow Control: A Case Study on Fuzzy Logic Application},
      journal = {International Journal of Transportation Engineering and Technology},
      volume = {3},
      number = {3},
      pages = {25-38},
      doi = {10.11648/j.ijtet.20170303.11},
      url = {https://doi.org/10.11648/j.ijtet.20170303.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijtet.20170303.11},
      abstract = {This work uses concepts, tools, and methodologies associated to Operational Research and Artificial Intelligence to turn more efficient a system that controls traffic lights at a road crossing. Using Operational Research, through Linear Programming method, the intelligent traffic light operation is described as a mathematical formulation and constraints. That information is used for MacVicar-Whelam table elaboration that relates system pertinence rules through fuzzy logic techniques. It is pled, with the described development, to obtain of solid results for validation of the developed methodology, as well as its efficient control of intelligent traffic lights.},
     year = {2017}
    }
    

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    T1  - Intelligent Urban Traffic Flow Control: A Case Study on Fuzzy Logic Application
    AU  - Wendell de Queiróz Lamas
    AU  - Giorgio Eugenio Oscare Giacaglia
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    JF  - International Journal of Transportation Engineering and Technology
    JO  - International Journal of Transportation Engineering and Technology
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.ijtet.20170303.11
    AB  - This work uses concepts, tools, and methodologies associated to Operational Research and Artificial Intelligence to turn more efficient a system that controls traffic lights at a road crossing. Using Operational Research, through Linear Programming method, the intelligent traffic light operation is described as a mathematical formulation and constraints. That information is used for MacVicar-Whelam table elaboration that relates system pertinence rules through fuzzy logic techniques. It is pled, with the described development, to obtain of solid results for validation of the developed methodology, as well as its efficient control of intelligent traffic lights.
    VL  - 3
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