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.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Lane change trajectory prediction using artificial neural network


    Contributors:


    Publication date :

    2013


    Size :

    22 Seiten, 16 Bilder, 1 Tabelle, 20 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Lane change trajectory prediction using artificial neural network

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


    Lane change trajectory prediction using artificial neural network

    Tomar, Ranjeet Singh | Online Contents | 2013


    Neural Network Based Lane Change Trajectory Prediction in Autonomous Vehicles

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


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

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

    Free access

    Lane change trajectory prediction by using recorded human driving data

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