The invention discloses a vehicle trajectory prediction method based on global attention and state sharing. The solution method comprises the following steps that a GAS-LED trajectory prediction model of a codec LSTM model with a global attention mechanism and state sharing is used; in the GAS-LED track prediction model, a state sharing mechanism with an encoder and a decoder is adopted to reduce the calculation workload, and meanwhile, two parallel calculation GAS-LED track prediction models are adopted to output prediction of the transverse lane changing behavior and the longitudinal driving distance of the vehicle in parallel; in the track prediction task of the lane level, the lane where the vehicle is located is focused on, and the GAS-LED track prediction model outputs corresponding prediction results for the transverse lane change and the longitudinal driving distance; and historical information of the current vehicle and the surrounding vehicles is used as the input of the GAS-LED trajectory prediction model 2, and then the two GAS-LED trajectory prediction models are used in parallel to obtain more output results convenient to predict. Through the scheme, the purpose of high-precision prediction is achieved, and the method has very high practical value and popularization value.

    本发明公开了一种基于全局注意力和状态共享的车辆轨迹预测方法,该解决方法包括使用具有全局注意力机制和状态共享的编解码器LSTM模型的GAS‑LED轨迹预测模型;在GAS‑LED轨迹预测模型中,采用具有编码器和解码器状态共享机制来减少计算工作量,同时采用两个并行计算的GAS‑LED轨迹预测模型来并行输出车辆横向变道行为和纵向行驶距离的预测;在车道级别的轨迹预测任务中,重点关注车辆所在的车道,GAS‑LED轨迹预测模型一对横向变道和纵向行驶距离输出相应预测结果;将当前车辆及其周围车辆的历史信息作为GAS‑LED轨迹预测模型二的输入,然后将两个GAS‑LED轨迹预测模型并行使用,以获得更多方便预测的输出结果。通过上述方案,本发明达到了高精度预测的目的,具有很高的实用价值和推广价值。


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    Titel :

    Vehicle trajectory prediction method based on global attention and state sharing


    Weitere Titelangaben:

    一种基于全局注意力和状态共享的车辆轨迹预测方法


    Beteiligte:
    LIU SHUNCHENG (Autor:in) / SU HAN (Autor:in) / ZHENG KAI (Autor:in) / ZHENG BOLONG (Autor:in)

    Erscheinungsdatum :

    01.06.2021


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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