Traffic flow forecasting has attracted much interest in current literature because of its importance in both the theoretical and empirical aspects of ITS deployment. Many models and methods have been presented in the past. But most of them regard the transportation system as the linear system and using the linear theory to predict the traffic flow. In fact, transportation system is a nonlinear system and traffic flow data exhibits chaotic properties. In this paper, we try to use the chaos theory to forecast the traffic flow in a short-term. Usually there is noise in the collected data which decrease the forecasting precision. So we denoise the data using wavelet transform before forecasting in this paper. The experiment is performed for inductance loop data collected in five minutes interval from the viaduct of Yan'an road in Shanghai in China. And at last our study concludes that techniques based on phase space reconstruction can be used to predict the traffic flow in a short-term. Furthermore, the prediction result is accurate and reliable.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    The study of short-term traffic flow forecasting based on theory of chaos


    Beteiligte:
    Jin Wang, (Autor:in) / Qixin Shi, (Autor:in) / Huapu Lu, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    984208 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    The Study of Short-Term Traffic Flow Forecasting Based on Theory of Chaos

    Wang, J. / Shi, Q. / Lu, H. et al. | British Library Conference Proceedings | 2005



    Ship short-term traffic flow fuzzy prediction method based on chaos theory

    CHEN TINGTING / GUO YUNLONG / RUI LEJUN | Europäisches Patentamt | 2020

    Freier Zugriff


    An applicable short-term traffic flow forecasting method based on chaotic theory

    Jianming Hu, / Chunguang Zong, / Jingyan Song, et al. | IEEE | 2003