The invention discloses a vehicle multi-modal trajectory prediction method based on an HGT network, and the method comprises the steps: firstly segmenting an Argover trajectory prediction data set, then carrying out the preprocessing, and storing the trajectory data and lane line data of a local space; an HGT network is constructed, and the local space fusion module encodes a vehicle interaction relationship, excavates a local interaction mode, extracts time features and captures dynamic changes of the time features; fusing vehicle time features, and interacting output features with environment features to enable the vehicle to sense environment changes and adjust behaviors; the environment sensing module captures the influence of surrounding environment characteristics on future behaviors of the vehicle; the global interaction module further improves the perception capability of the vehicle on the influence of surrounding vehicles from a global perspective; and the track decoding module is used for decoding the vehicle characteristics by using the multi-layer perceptron to generate a predicted track and calculating a score to evaluate the quality of the predicted track. According to the invention, multi-mode trajectory prediction can be carried out on the surrounding vehicles of the autonomous vehicle, and an accurate and stable future trajectory is generated.

    本发明公开了一种基于HGT网络的车辆多模态轨迹预测方法,首先对Argoverse轨迹预测数据集进行分割,然后进行预处理,保存局部空间的轨迹数据和车道线数据;构建HGT网络,其中,局部空间融合模块对车辆交互关系编码,挖掘局部交互模式,同时提取时间特征捕捉其动态变化;然后融合车辆时间特征,并将输出特征与环境特征交互,使车辆感知环境变化并调整行为;环境感知模块捕捉周边环境特征对车辆未来行为的影响;全局交互模块从全局视角进一步提升车辆对周围车辆影响的感知能力;轨迹解码模块,用多层感知机解码车辆特征生成预测轨迹,并计算得分评估预测轨迹的质量。本发明能够对自动驾驶汽车的周围车辆进行多模态轨迹预测,生成了准确而稳定的未来轨迹。


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    Titel :

    Vehicle multi-modal trajectory prediction method based on HGT network


    Weitere Titelangaben:

    一种基于HGT网络的车辆多模态轨迹预测方法


    Beteiligte:
    GAO SHANGBING (Autor:in) / WANG HAO (Autor:in) / FENG YIXIN (Autor:in) / WANG TENG (Autor:in) / ZHAO KEFAN (Autor:in) / ZHANG HAIYAN (Autor:in) / WANG YUANYUAN (Autor:in) / BAI ANMING (Autor:in) / GAO JUNJIE (Autor:in)

    Erscheinungsdatum :

    30.05.2025


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / 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 / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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