TRAFFIC FLOW FORECASTING FOR INTELLIGENT TRANSPORTATION SYSTEMS

This paper reports on a project which investigated the feasibility of forecasting freeway traffic flow and developing a framework in which to use a forecasting capability in Intelligent Transportation Systems (ITS) traffic management and traveler information services. Four models were developed and tested on two sites on the Capital Beltway in Northern Virginia. The models were the historical average, time series, neural network, and nonparametric regression models. The nonparametric regression model significantly outperformed the others. An ITS system architecture was also developed to take full advantage of the model's forecasting capability.