Modeling Traffic Volume Based on Highway Toll Database Using GM (1,1)

Abstract

To circumvent the poor prediction accuracy of traffic volume models available due to the lack of traffic data and inaccurate judgments on the traffic influence factors, in this paper we established a traffic volume prediction model using grey forecasting model GM(1,1) based on the real traffic data from the highway toll database. The GM(1,1) method has advantage of the strong adaptiveness to Complex system, thus getting a great advantage over other methods for modeling such a complex nonlinear traffic volume system with many uncertain influence factors. Simulation results show that our GM(1,1) model has mean relative prediction error of 3.9%, which accomplishes our intended prediction accuracy.