This paper works on the short-term travel time prediction, aiming at predicting dynamically (or fixed-frequency) by considering dynamic road traffic index volatility and average speed, and then providing the real-time travel time prediction for users in advance. This paper improves the prediction algorithm, referenced to current traffic parameters prediction methods basing on Kalman filter, and solves the time lag and the automatic update of historical average data needed. Then this paper uses 4 evaluation indexes to make known the degree of deviation and goodness of fit between predictive value and actual value, and to verify that improved algorithm could make predictive travel time more accordant with the practical situation.


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    Titel :

    Short-Term Travel Time Prediction for a Car Dynamic Navigation System


    Beteiligte:
    He, Yuxi (Autor:in) / Du, Renjie (Autor:in) / Zou, Tong (Autor:in) / Zhang, Nian (Autor:in) / Gao, Xunfei (Autor:in)

    Kongress:

    Fifth International Conference on Transportation Engineering ; 2015 ; Dailan, China


    Erschienen in:

    ICTE 2015 ; 1738-1744


    Erscheinungsdatum :

    25.09.2015




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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