Journals / Electronic Letters on Science and Engineering / 2009 / Cilt: 5 - Sayı: 1

Vehicular Delay Modeling at Signalized Intersections with Fuzzy Logic and Artificial Neural Networks

Bulanık Mantık ve Yapay Sinir Ağı ile Sinyalize Kavşaklardaki Taşıt Gecikmelerinin Modellenmesi

Pages
11–18
Publication Date
2009-04-01
DOI
—
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AI Summary & Key Takeaways

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

Our model is compared with conventional delay calculation methods and another project that is about delaying at signalized intersections.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Delaying at signalized intersections is an important point for controlling traffic movement in a city.
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Key Findings & Data:In this project ,we designate the vehicular delay model at signalized intersections by using fuzzy logic and artificial neural Networks.
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Conclusion & Impact:Our model is compared with conventional delay calculation methods and another project that is about delaying at signalized intersections.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Sinyalize kavşak · taşıt gecikmesi

Abstract

Delaying at signalized intersections is an important point for controlling traffic movement in a city. In this project ,we designate the vehicular delay model at signalized intersections by using fuzzy logic and artificial neural Networks. Our model is compared with conventional delay calculation methods and another project that is about delaying at signalized intersections.

Özet

Kent içi trafik akımının yönetilmesinde kavşaklardaki araç gecikmesi yeterince önemsenmesi gereken bir husustur. Bu çalışmada sinyalize kavşaklardaki araç gecikmesini bulanık mantık ve yapay sinir ağı teknikleri ile modelleyeceğiz. Bu alanda daha önceden yapılan çalışma ve geleneksel yöntemler ile sonuçlarımızın karşılaştırılması yapılacaktır. Ayrıca kullanacağımız yapay sinir ağı ile probleme başka bir yaklaşım açısı getirilmesi amaçlanmıştır.

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Cite This Article

Mutlu, E., Yavuz, M. E. (2009). Vehicular Delay Modeling at Signalized Intersections with Fuzzy Logic and Artificial Neural Networks. Electronic Letters on Science and Engineering, Cilt: 5 - Sayı: 1, 11–18. https://ajindex.com/articles/133685

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