Real time traffic signal timing approach based on artificial neural network

Ali Tahir KARAŞAHİN; Abdullah Erdal TÜMER

Makale detayları

Real time traffic signal timing approach based on artificial neural network

Yazarlar:

Ali Tahir KARAŞAHİN | Abdullah Erdal TÜMER

Yayıncı:

Kyrgyz-Turkish Manas University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

MANAS Journal of Engineering 2020 Vol.8 Issue 1, pp.49-54

Belge Tipi:

Makale

Yayın Tarihi:

6/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000527894

Sıklık:

İki Yıllık

eISSN:

1694-7398

pISSN:

1694-7398

Özet:

 

As the population increases, is more and more increasing the number of vehicles in cities. The increasing number of vehicle make traffic management complicated. Difficult traffic management leads to more fuel consumption, CO2 and other harmful emissions. Therefore, real-time optimization of traffic lights (signaling) used in traffic management can make traffic management more efficient. In this study, green light time is optimized by estimating the number of vehicles in an intersection with signal lights in Konya city center through artificial neural network. The results are evaluated with different performance criteria and it has been shown that the developed estimation model can be successfully used to optimize the green light durations.

Makale detayları

Real time traffic signal timing approach based on artificial neural network

Yazarlar: Ali Tahir KARAŞAHİN | Abdullah Erdal TÜMER

Yayıncı: Kyrgyz-Turkish Manas University

Ana Başlıklar: Uygulamalı fizik

Dergi: MANAS Journal of Engineering 2020 Vol.8 Issue 1, pp.49-54

Belge Tipi: Makale

Yayın Tarihi: 6/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000527894

Sıklık: İki Yıllık

eISSN: 1694-7398

pISSN: 1694-7398

Sayı

Yazarlar:

Ali Tahir KARAŞAHİN | Abdullah Erdal TÜMER

Yayıncı:

Kyrgyz-Turkish Manas University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

MANAS Journal of Engineering 2020 Vol.8 Issue 1, pp.49-54

Belge Tipi:

Makale

Yayın Tarihi:

6/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000527894

Sıklık:

İki Yıllık

eISSN:

1694-7398

pISSN:

1694-7398