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Using a Hierarchical Fuzzy System for Traffic Lights Control Process

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10245))

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Abstract

The present study presents the applications of a hierarchical fuzzy system in the traffic light system control process. In this paper a hierarchical fuzzy system was designed. This system is based on the fuzzy system for traffic lights control FS-TLC. The main advantage of the solution presented herein is a significant reduction of the number of defined rules. Additionally, owing to the use of hierarchical fuzzy systems, it is possible to greatly reduce the time required for computations and to reduce the use of memory in the systems designed. Also that systems can be significantly more effective in operation, and they allow a creation of faster controllers that may be implemented in the hardware architecture.

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References

  1. Cox, E.: The Fuzzy Systems Handbook, Second Edition: A Practitioner’s Guide to Building, Using, and Maintaining Fuzzy Systems. Academic Press, London (1999)

    Google Scholar 

  2. Pedrycz, W., Gomide, F.: Fuzzy Systems Engineering: Toward Human-Centric Computing. Wiley-IEEE Press, USA (2007)

    Book  Google Scholar 

  3. Klir, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice Hall, Upper Saddle River (1995)

    MATH  Google Scholar 

  4. Mendel, J.M.: Uncertain rule-based fuzzy logic: introduction and new directions. Prentice Hall, Upper Saddle River (2000). McCluskey, E.J.: Minimization of boolean function. Bell Syst. Tech. J. 35(5), 1417–1444 (1956)

    MATH  Google Scholar 

  5. Poletajew, B., Slowik, A.: An application of fuzzy logic to traffic lights control and simulation in real time. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS (LNAI), vol. 9692, pp. 266–275. Springer, Cham (2016). doi:10.1007/978-3-319-39378-0_23

    Google Scholar 

  6. Aksac, A., Uzun, E., Ozyer, T.: A real time traffic simulator utilizing an adaptive fuzzy inference mechanism by tunning fuzzy parameters. Springer Science+ Business Media, pp. 698–720, LLC (2011)

    Google Scholar 

  7. Lee, M.-L., Chung, H.-Y., Yu, F.-M.: Modeling of hierarchical fuzzy systems. Department of Electrical Engineering, National Central University, Chung-Li 32054, Taiwan, ROC

    Google Scholar 

  8. Renkas, K., Niewiadomski, A.: Hierarchical fuzzy logic systems and controlling vehicles in computer games. J. Appl. Comput. Sci. 22(1), 201–212 (2014)

    Google Scholar 

  9. Renkas, K., Niewiadomski, A.: Learning rules for hierarchical fuzzy logic systems using wu & Mendel IF-THEN rules quality measures. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds.) ICAISC 2016. LNCS, vol. 9692. Springer, Cham (2016)

    Google Scholar 

  10. Torra, V.: A review of the construction of hierarchical fuzzy systems. Int. J. Intell. Syst. 17(5), 531–543 (2002)

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics and Computer Science, Koszalin University of Technology, Sniadeckich 2 Street, 75-453, Koszalin, Poland

    Bartosz Poletajew & Adam Slowik

Authors
  1. Bartosz Poletajew
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  2. Adam Slowik
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Corresponding author

Correspondence to Bartosz Poletajew .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Poletajew, B., Slowik, A. (2017). Using a Hierarchical Fuzzy System for Traffic Lights Control Process. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_26

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  • DOI: https://doi.org/10.1007/978-3-319-59063-9_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59062-2

  • Online ISBN: 978-3-319-59063-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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