Abstract The traffic flow prediction plays a key role in modern Intelligent Transportation Systems (ITS). Although great achievements have been made in traffic flow prediction, it is still a challenge to improve the prediction accuracy and reduce the operation time simultaneously. In this paper, we proposed a hybrid prediction methodology combined with improved seasonal autoregressive integrated moving average (ISARIMA) model and multi-input autoregressive (AR) model by genetic algorithm (GA) optimization. Since traffic flow data has strong spatio-temporal correlation with neighboring stations, GA is used to select those stations which are highly correlated with the prediction station. The ISARIMA model is used to predict the traffic flow in test station at first. A multiinput AR model with traffic flow data in optimal selected stations is built to predict the traffic flow in test station as well. The final prediction result can be gained by combining with the results of ISARIMA and multi-input AR model. The test results from traffic data provided by TDRL at UMD Data Center demonstrate that proposed algorithm has almost the same prediction accuracy with artificial neural networks (ANNS). However, its operation time is almost the same with SARIMA model. It is proved to be an effective method to perform traffic flow prediction.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An Algorithm for Traffic Flow Prediction Based on Improved SARIMA and GA


    Beteiligte:
    Luo, Xianglong (Autor:in) / Niu, Liyao (Autor:in) / Zhang, Shengrui (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2018




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.80 Verkehrswesen, Transportwesen: Allgemeines, Verkehrswesen, Transportwesen: Allgemeines / 74.75 Verkehrsplanung, Verkehrspolitik, Verkehrsplanung, Verkehrspolitik / 55.80 Verkehrswesen, Transportwesen: Allgemeines / 56.24 Straßenbau, Straßenbau / 56.24 Straßenbau / 74.75 Verkehrsplanung, Verkehrspolitik



    An Algorithm for Traffic Flow Prediction Based on Improved SARIMA and GA

    Luo, Xianglong / Niu, Liyao / Zhang, Shengrui | Springer Verlag | 2018


    Short-term traffic flow prediction system based on SARIMA-GA-Elman combined model

    ZHANG XIJUN / WANG CHENHUI / TAO YE et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Road monthly traffic volume prediction method based on SARIMA-NAR combined model

    WANG YOU / JIA RUXUE / YE YUNXIA et al. | Europäisches Patentamt | 2021

    Freier Zugriff


    Multivariate Traffic Forecasting Technique Using Cell Transmission Model and SARIMA Model

    Szeto, W.Y. / Ghosh, B. / Basu, B. et al. | British Library Online Contents | 2009