Dergiler / International Journal of Computational and Experimental Science and Engineering / 2020 / Cilt: 6 - Sayı: 2

The Determination of the Uniformity in Road Lighting Using Artificial Neural Networks

Sayfa
127–131
Yayın Tarihi
2020-07-31
DOI
—
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The uniformity results of the test roads were examined to meet the standards according to the road class.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:To ensure that drivers can travel safely, it is necessary to provide good visibility conditions of the road lighting.
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Temel Bulgular & Veri:Thanks to good road lighting, accident rates will decrease, pedestrians' safety will be increased and drivers will be able to travel comfortably.
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Sonuç & Katkı:The uniformity results of the test roads were examined to meet the standards according to the road class.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Road Lighting · Uniformity · Artificial Neural Network

Abstract

To ensure that drivers can travel safely, it is necessary to provide good visibility conditions of the road lighting. Thanks to good road lighting, accident rates will decrease, pedestrians' safety will be increased and drivers will be able to travel comfortably. Road lighting standards are included in CIE's 115 “Recommendations for the Lighting of Roads for Motor and Pedestrian Traffic”. According to this standard, there are 6 different lighting classes according to the road definition. There are different lighting standards for each class. These are: average luminance (Lave), overall uniformity (U0), longitudinal uniformity (U1), disability glare (TI), lighting of surroundings (SR). Uniformity is a measurement of how equally light is distributed on the road. Overall uniformity ratio is of minimum luminance to mean luminance and longitudinal uniformity is the ratio of minimum luminance to maximum luminance. If the uniformity is good, all objects on the road can be easily seen by drivers. In this study, a new method was used to measure the uniformity of the road. Unlike classical methods, image processing and artificial intelligence techniques are used to calculate luminance and uniformity. The uniformity results of the test roads were examined to meet the standards according to the road class.

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Bu Makaleye Atıf Yap

KAYAKUŞ, M., ÜNCÜ, İ. S. (2020). The Determination of the Uniformity in Road Lighting Using Artificial Neural Networks. International Journal of Computational and Experimental Science and Engineering, Cilt: 6 - Sayı: 2, 127–131. https://ajindex.com/articles/765794

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Kaynakça (5)

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