In this paper, the effectiveness of lane change (LC) trajectory prediction on the basis of past motion parameters of LC vehicle is studied. A vehicle's LC trajectory is modelled as a time series and back propagation neural network is used for short-range and long-range prediction. Results using field data indicate that future LC trajectory cannot be predicted with sufficient accuracy using past motion parameters of the vehicle only. The results also show variation in the change of motion parameters during LC. This suggests external neighbourhood influence and need for incorporating this to increase the accuracy of forecasting.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Lane change trajectory prediction using artificial neural network


    Beteiligte:


    Erscheinungsdatum :

    2013


    Format / Umfang :

    22 Seiten, 16 Bilder, 1 Tabelle, 20 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    Lane change trajectory prediction using artificial neural network

    Tomar, Ranjeet Singh | Online Contents | 2013


    Lane change trajectory prediction using artificial neural network

    Tomar,R.S. / Verma,S. / Indian Inst.of Information Technol.Allahabad,IN | Kraftfahrwesen | 2013


    Neural Network Based Lane Change Trajectory Prediction in Autonomous Vehicles

    Tomar, Ranjeet Singh / Verma, Shekhar | Tema Archiv | 2011


    An Automated Lane-Change System Based on Probabilistic Trajectory Prediction Network

    Ahn, Yoonyong / Han, Sangwon / Sung, Jihoon et al. | Springer Verlag | 2024

    Freier Zugriff

    Lane change trajectory prediction by using recorded human driving data

    Yao, Wen / Zhao, Huijing / Bonnifait, Philippe et al. | IEEE | 2013