The invention discloses a motion trail prediction method and device based on a dynamic local map, equipment and a medium. The method is characterized by comprising the following steps: acquiring historical motion track information and map information of a target vehicle, and respectively performing data extraction on the historical motion track information and the map information through a preset feature encoder to obtain a track feature vector and a map feature vector; performing feature fusion on the track feature vector and the map feature vector through a preset feature fusion device to obtain a map fusion vector, and performing feature fusion on the map fusion vector and the track feature vector to obtain a track fusion vector; and predicting the motion trajectory of the target vehicle according to the trajectory fusion vector to obtain a trajectory prediction result of the target vehicle. Accurate prediction of the motion track of the target vehicle is realized, the prediction accuracy is improved by considering fusion of multiple vectors, the influence of other interference factors in the road on motion prediction is reduced, and the prediction accuracy is improved.
本发明公开了一种基于动态局部地图的运动轨迹预测方法、装置、设备和介质。其特征包括:获取目标车辆的历史运动轨迹信息和地图信息,通过预设的特征编码器分别对所述历史运动轨迹信息和所述地图信息进行数据提取,得到所述轨迹特征向量和地图特征向量;通过预设的特征融合器对所述轨迹特征向量和所述地图特征向量进行特征融合得到地图融合向量,对所述地图融合向量和所述轨迹特征向量进行特征融合得到轨迹融合向量;根据轨迹融合向量对目标车辆的运动轨迹进行预测,得到目标车辆的轨迹预测结果。实现了对目标车辆运动轨迹的准确预测,通过考虑多个向量的融合提高了预测精准度,减少了道路中其他干扰因素对运动预测的影响,提高了预测准确性。
Motion track prediction method and device based on dynamic local map, equipment and medium
基于动态局部地图的运动轨迹预测方法、装置、设备和介质
27.10.2023
Patent
Elektronische Ressource
Chinesisch
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 / G01C Messen von Entfernungen, Höhen, Neigungen oder Richtungen , MEASURING DISTANCES, LEVELS OR BEARINGS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06V |
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