Accurate short-term traffic flow forecasting contributes a crucial element to the dynamic operations of traffic management and control systems. This research developed a multivariate ARIMAX model that incorporates related exogenous upstream flows {X} and an univariate SARIMA model to generate forecasts. Traffic data from the freeways A3 and A5 near Frankfurt, Germany were used for an empirical study. The estimation results show that the transfer function in the ARIMAX model gives a relationship conforming to the kinematic wave theory. The forecasting evaluations present that the multivariate ARIMAX model performs more accurate than the SARIMA model has. This result infers that the use of upstream traffic flows is effective in time series modeling for short-term traffic flow forecasting. The ARIMAX model should be used if time series analysis is adopted for short-term traffic flow forecasting.


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    Title :

    Short-term Freeway Traffic Flow Forecasting with ARIMAX Modeling


    Additional title:

    Kurzfristige Prognose der Verkehrsstärke der Autobahn mit ARIMAX Modell


    Contributors:

    Publication date :

    2010



    Type of media :

    Miscellaneous


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    625 / 388