The short-term forecast of traffic flow is the foundation of a successful control and route guidance in intelligent transport systems (ITS). Many attempts on the forecast methods have been done in recent years. The effort of this paper focus on the short-term predictability of traffic flow what determines whether the same or similar methods applied in middle or long term forecast is also effective to short term. After the relation among the predictability, self-similarity and fractal is explained in the paper, an approach to verify the existence of self-similarity in traffic system based on the state space reconstruction is proposed and a practical example on this method is given.


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    Titel :

    The Short-Term Predictability of Traffic Flow


    Beteiligte:
    Ma, Shoufeng (Autor:in) / He, Guoguang (Autor:in) / Du, Lanpu (Autor:in)

    Kongress:

    Second International Conference on Transportation and Traffic Studies (ICTTS ) ; 2000 ; Beijing, China



    Erscheinungsdatum :

    12.07.2000




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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