Application of Univariate Time Series Theory to Passenger Demand Forecasting

Abstract

The methods, which are used for the purpose of passenger demand forecasting by Slovak transportation companies at the present time, are considerably simplified, and what is more, they are not already considered to be accurate. These limitations might be caused by insufficient research in this area over last years. Purpose of this paper is to identify a statistical model of passenger demand for suburban bus transport which satisfies the statistical significance of its parameters and randomness of its residuals. Three different methodologies – exponential smoothing, multiple linear regression and autoregressive models were used in order to identify more accurate and reliable statistical model compared with nowadays used ones.