Accurate short-term traffic flow prediction is the foundation of the efficient and proactive management of freeway networks, especially on the abnormal traffic states. The relationship between traffic flow on the current section and the upstream stations can be used for predicting short-term traffic flow. In this paper, we reveal this relationship by the traffic flow structure pattern. The structure pattern can be drawn from real freeway toll data and a few video detective cameras on the freeway segments. Based on the stability pattern, a new traffic flow prediction algorithm has been proposed. Experimental based on real data showed that the prediction method based on structure pattern is an effective approach for traffic flow prediction, especially on the abnormal traffic state.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A short-term freeway traffic flow prediction method based on road section traffic flow structure pattern


    Beteiligte:
    Zhang, Ping (Autor:in) / Xie, Kunqing (Autor:in) / Song, Guojie (Autor:in)


    Erscheinungsdatum :

    01.09.2012


    Format / Umfang :

    1105056 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Short-Term Freeway Traffic Flow Prediction: Bayesian Combined Neural Network Approach

    Zheng, W. / Lee, D.-H. / Shi, Q. | British Library Online Contents | 2006


    Short-Term Traffic Prediction considering Spatial-Temporal Characteristics of Freeway Flow

    Jiaqi Wang / Yingying Ma / Xianling Yang et al. | DOAJ | 2021

    Freier Zugriff


    Short-term freeway traffic flow forecasting with ARIMAX modeling

    Lee, Ming-Tsung | TIBKAT | 2010

    Freier Zugriff