A multi-modal vehicle trajectory prediction method based on a graph interaction mechanism relates to the technical field of automatic driving, and comprises the following steps: constructing a deep learning database containing vehicle trajectory data, and dividing the deep learning database into a training set and a verification set; the method comprises the following steps: defining a vehicle trajectory prediction task, acquiring historical trajectory information and lane information of a target vehicle, encoding input information by using an LSTM encoder, processing vehicle interaction by using a multi-modal attention model, and extracting local features of lane and vehicle interaction by using a multi-modal attention model. And decoding by using a Bezier curve-based trajectory decoder to obtain a vehicle trajectory prediction model. According to the method, the attention capability of the model on important information is enhanced through the graph modeling interaction relationship, capturing the complex association between the tracks and combining with a multi-head attention mechanism, and the continuous track decoder based on the Bezier curve is introduced to decode the track prediction, so that the smooth and coherent tracks can be effectively generated; therefore, the prediction accuracy and feasibility are improved.

    一种基于图交互机制的多模态车辆轨迹预测方法,涉及自动驾驶技术领域,包括:构建一个包含车辆轨迹数据的深度学习数据库,将其划分为训练集和验证集;定义车辆轨迹预测任务,获取历史轨迹信息和目标车辆的车道信息,利用LSTM编码器对输入信息进行编码,采用图多头注意力模型处理车辆交互,使用多模态注意力模型以提取车道和车辆交互的局部特征,使用基于贝塞尔曲线的轨迹解码器进行解码,获得车辆轨迹预测模型。本发明通过图建模交互关系,捕捉轨迹之间的复杂关联,结合多头注意力机制,增强模型对重要信息的关注能力,引入了基于贝塞尔曲线的连续轨迹解码器进行轨迹预测的解码,能够有效地生成平滑且连贯的轨迹,从而提高预测的准确性和可行性。


    Access

    Download


    Export, share and cite



    Title :

    Multi-modal vehicle trajectory prediction method based on graph interaction mechanism


    Additional title:

    一种基于图交互机制的多模态车辆轨迹预测方法


    Contributors:
    GAO JIANPING (author) / YANG YU (author) / LIU PAN (author) / ZHANG ZHIJUN (author) / XIE CHENGWEI (author)

    Publication date :

    2024-12-27


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



    Multi-modal trajectory prediction method

    JIANG WENJUAN / JIN ZHI / WANG REN et al. | European Patent Office | 2023

    Free access

    Multi-modal trajectory prediction method based on vehicle interaction diagram space-time decoupling coding

    TANG XIAOLIN / ZHANG KUNYI / CHEN ZHIGE et al. | European Patent Office | 2025

    Free access


    Multi-modal vehicle trajectory prediction based on mutual information

    Fei, Cong / He, Xiangkun / Ji, Xuewu | IET | 2020

    Free access

    End-to-end multi-modal trajectory prediction method based on dynamic graph convolution

    LI HAISHENG / MA HUIJIA | European Patent Office | 2024

    Free access