Prediction of traffic intensity for dynamic street lighting

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.