Along with the development of Intelligent Transportation System, traffic detectors collect numerous transportation state data in information databases and accumulate. Such data is greatly meaningful to the vehicle navigation. In this paper, we propose a noble two-stage algorithm about vehicle navigation by using data mining methods on the historical and current transportation dataset. This algorithm begins with picking sensitive data about start and end point in an urban traffic network, and data from related (or nearest) road fragments. Referring to current time and season, the algorithm gives an evaluation to every related road fragments and outputs a most reasonable route between start and end point. The experimental and theoretical analyzes show that this algorithm can form an efficient and effective route in reasonable time.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Two-Stage Data Mining Based Vehicle Navigation Algorithm in Urban Traffic Network


    Beteiligte:
    Li, Xian-Tong (Autor:in) / An, Shi (Autor:in)


    Erscheinungsdatum :

    2012


    Format / Umfang :

    5 Seiten




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch





    A Data Mining Based Algorithm for Traffic Network Flow Forecasting

    Gong, X. / Liu, X. / IEEE | British Library Conference Proceedings | 2003


    Data mining based research on urban tide traffic problem

    Gong, Xiaoyan / Lu, Yu | Tema Archiv | 2008



    Urban road network main traffic flow path mining method based on AVI data

    CHEN PENG / XU JIAMING | Europäisches Patentamt | 2023

    Freier Zugriff