The invention discloses a target object track prediction method and device, a storage medium and electronic equipment, and the method comprises the steps: determining a target object of which the track needs to be predicted and each obstacle, determining the features of the target object and the features of each obstacle according to the historical dynamic information of the target object and each obstacle; and the target object feature and each obstacle feature are input into each node of a directed graph in the graph neural network, the features of each node are aggregated through weights among the nodes, and the aggregated target nodes are input into a processing layer of the graph neural network to obtain a future trajectory of the target object. According to the method, the graph neural network containing the directed graph is used for predicting the future trajectory of the target object, and in the process of using the graph neural network, the features of the target object and the features of all obstacles are aggregated through the directed graph in the graph neural network, that is, historical motion information of the target object is considered, so that the target object is more accurate. And historical motion information of each obstacle is also considered, so that the accuracy of predicting the future trajectory of the target object is improved.
本说明书公开了一种目标物轨迹预测方法、装置、存储介质及电子设备,确定需要预测轨迹的目标物以及各障碍物,根据目标物与各障碍物的历史动态信息,确定目标物特征以及各障碍物特征,并将目标物特征以及各障碍物特征输入图神经网络中的有向图的各节点中,通过各节点之间的权重,对各节点的特征进行聚合,将聚合后的目标节点输入图神经网络的处理层,得到目标物的未来轨迹。本方法使用包含有向图的图神经网络对目标物的未来轨迹进行预测,在使用图神经网络的过程中,通过图神经网络中的有向图对目标物的特征以及各障碍物的特征进行聚合,即考虑了目标物自身的历史运动信息,还考虑到了各障碍物的历史运动信息,提高了预测目标物未来轨迹的准确性。
Target object track prediction method and device, storage medium and electronic equipment
一种目标物轨迹预测方法、装置、存储介质及电子设备
2022-03-18
Patent
Electronic Resource
Chinese
IPC: | 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 |
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