Prediction of Traffic Intensity for Dynamic Street Lighting

Abstract

Abstract-In this paper, the problem of short-term prediction of traffic flow in a city traffic network is considered. This prediction is performed in order to provide input data to a dynamic control system for street lighting. The forecasting is done by a multi-layer using artificial neural network. Because of the limited number of sensors, the data is insufficient to describe the relation between the traffic intensity at a given point and the points in which the flow intensity is measured. The proposed approach is tested by using data from the centre of Kraków. The prediction error turned to be low.

Comparative Study of Road Lighting Efficiency in the Context of CEN/TR 13201 2004 and 2014 Lighting Standards and Dynamic Control

“…Optimization of lighting design and management, in particular, is improving the design process [8][9][10], or introducting a dynamic control based on real-time data from sensors, e.g., traffic intensity [11][12][13], supported by mathematical models [14].…”