Trajectory prediction is very important for autonomous driving vehicles. Deep-learning approaches can capture the interaction information. Therefore more and more researchers are using deep-learning models to accomplish vehicle trajectory prediction. This paper provides a detailed and comparative description of the methods for vehicle trajectory prediction based on deep-learning models. We start by modelling trajectory predictions for vehicles. Several common deep-learning models used in vehicle trajectory prediction are then highlighted. Next, we compare the structural features, salient advantages and applicable scenarios of commonly used deep-learning models. Future directions for vehicle trajectory prediction are discussed at the end.


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    Title :

    A Survey of Vehicle Trajectory Prediction Based on Deep-Learning


    Contributors:
    Yin, Huilin (author) / Wen, Yurong (author) / Li, Jiaxiang (author)


    Publication date :

    2023-02-24


    Size :

    1223213 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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