SavedAdd your journal

Journals / Politeknik Dergisi / 2000 / Cilt: 3 - Sayı: 3

Software in fuzzy logic for traffic control of the intersection

Bulanık mantık ile kavşaklarda trafik denetimi sağlayan yazılım

O. Ayhan ERDEM
Pages
87–96
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The fuzzy logic control proved to be a better method of control than conventional control methods.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Fuzzy Logic Control can be used as an alternative method for the control of traffic environments in the intersections.
📊
Key Findings & Data:A typical cross intersection was chosen for the traffic environment and the performance of the fuzzy logic controller was compared with the performance of conventional control.
💡
Conclusion & Impact:The fuzzy logic control proved to be a better method of control than conventional control methods.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Fuzzy Logic Control can be used as an alternative method for the control of traffic environments in the intersections. This paper presents the fuzzy-logic computer program which was constructed for a model traffic environment. A typical cross intersection was chosen for the traffic environment and the performance of the fuzzy logic controller was compared with the performance of conventional control. The fuzzy logic control proved to be a better method of control than conventional control methods.

Özet

Bulanık mantık kontrol, kavşaklarda trafik düzenlemesinin denetimi için alternatif bir metod olarak kullanılabilir. Bu makalede bulanık mantık denetiminin bilgisayar programı, bir model trafik düzenlemesi için oluşturulmuştur. Model olarak seçilen (Örnek: Kızılay kavşağı) tipik kavşaktaki trafik düzen ve performansı, geleneksel metodlarla yapılan denetimler ile karşılaştırılmıştır. Bulanık mantık metodu ile yapılacak kavşak trafik denetiminin geleneksel metodlara göre daha iyi olduğu ispatlanmaya çalışılmıştır.

🔖

Cite This Article

ERDEM, O. A. (2000). Software in fuzzy logic for traffic control of the intersection. Politeknik Dergisi, Cilt: 3 - Sayı: 3, 87–96. https://ajindex.com/articles/307324

References (2)

  1. Shimizu, H., Davidson, E.J., "Traffic Congession Control of Network, pp 117-122 2. Luk, J.Y.K, "Two traffic responsive area traffic control methods: Scat and Scoot", Traffic Engineering and Control, pages 14-20, 1984. 3. Nainar, I., Mohammadian, M., and Miller, J., "Adaptive control of traffic signal using fuzzy logic and genetic algorithms". Proceedings of 4th International Conference on Control, Automation, Robotics and Vision, 1:573-577,
  2. Singapore, December 1996. 4. R.N. Lea, J. Hoblit & J. Jani: 'Performance Comparision of A Fuzzy Logic Based Attinude Controler With the Shuttle On-Orbit Digital Auto Pilot' Proceedings of North American Fuzzy Information Processing Society (NAFIPS -91) Workshop, Columbia, May 14-17,1991. 5. Ellen, H.," A logical Structure For A Knowledge Base, Institue of Informatics, University of Oslo, Box 1080 Blindern, 0316 Oslo3, Norway. 6. Yan, J., Ryan, M., Power, J. Using Fuzzy Logic, Towards intelligent systems. 1994. 7. Günal, Ü., Bulanık Mantık, EMPA İleri Teknolojileri Bölümü, Otomasyon Dergisi, Ocak-Şubat 1998. 8. Günal, Ü., "Bulanık Mantık", Türkiye'de ve Dünyada Otomasyon, Sayı: 55-57, Sayfa: 170- 173,1997 9. T. Tilli (Çev. F. Meriçer), "Fuzzy: Bulanık Mantık", ELO Eloktronik, Sayı: 81-82, Sayfa: 19-25, 1995 10. Proceeding of the Industrial Conference on Fuzzy Systems ICFS-91, sponsored by The Microelectronics and Computer Technology Corparation, Austin, Texas, June 27-28, 1991. 11. Proceeding of the 1st International Workshop on Industrial Applications of Fuzzy Control and Intelligent Systems, sponsored by Center for Fuzzy Logic and Intelligent Systems Research, Texas A&M University, Collage Station, Texas, Nov 21-22, 1991 12. Mangold, M., Trâger, K., Lindenbach, A.: Wirksamkeit von Streckenbeeinflussungsanlagen unter besonderer Berücksichtigung der Umfelddatenerfassung (Efficacy of traffic control systems focusing on the Detection of Environmental Data), Research Work for the Ministry of Traffic, Kassel 1996 13. Zimmermann, H.- J.: Fuzzy Set Theory and Its Applications, Kluwer, Bosten, 1991 14. Laszio, T., "Fuzzy If.Then Rule Models and Their Tranformation Into One Another. IEEE Transaction on systems, man, and Cybernetics-Part A: Systems and Humans, Vol.26.No.5. September 1996 15. Von Altrock, C., "Fuzzy Logic and Neuro Fuzzy Applications Explained", Prentice Hall, ISBN 0-13-368456-2(1995). 16. Bağcioğullari Funda, Fuzzy Kümeler, sh 6-8, 1995 17. Novak, V., Fuzzy Sets and Their Applications, Adam Higer Bristol and