Identifying the Optimum Forecasting Horizon to Apply the Singular Spectrum Analysis on Daily Road Traffic Volume Forecasts

Abstract

The paper delivers an assessment of Singular Spectrum Analysis (SSA) forecasting ability for short- and medium-term forecasting horizon, on real time traffic volume data. The key study goal is to estimate forecasting pertinency for daily traffic volume, based upon measurements at toll station. The suggested methodology is tested on real data from Moschohorion and Pelasgia Toll Station – Greece, utilizing custom developed forecasting software toolbox. Applied research results confirm an advanced forecasting ability of proposed methodology for short-term forecasting horizon against medium term forecasting horizon, when performance is compared upon the statistical criteria of the coefficient of determination R2. The obtained results present that SSA forecasting model could provide a competent forecasting methodology for road traffic volume data.