Comparison of Road Luminance Data Estimated by Fuzzy Logic and ANN, A Case study of Kocaeli Sakıp Sabancı Street

Abstract

Road lighting constitutes the most important part of city lighting. While correct road lighting solves the chaos in transportation, it also paves the way for smooth urban traffic flow. It also allows people to have a comfortable and safe journey. In order to reduce accidents in the evening hours, safe driving and visual comfort must be provided to drivers. Just like inadequate road lighting, excessive lighting also causes accidents and waste of electrical energy. Good visibility of objects on the road and visual comfort for drivers is possible by ensuring an equal brightness distribution on the road surface. In this article, a prediction model was created with Artificial Neural Network (ANN) and Fuzzy Logic (FL) methods to find the luminance values of the road in Sakıp Sabancı street in Kocaeli province. When the predictions obtained by ANN and FL were compared, the results were seen to be accurate and compatible. When the estimation results obtained as a result of the application were examined, it was observed that the estimation of luminance values in good and qualified road lighting could be achieved with these methods.

Keywords

• Road Lighting
• Luminance
• Fuzzy Logic
• ANN

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