The invention relates to the technical field of intelligent networked automobiles, in particular to an intelligent networked automobile real-time track prediction method based on an improved neural network, which comprises the following steps: S1, modeling a scene graph of an intersection of a road and determining a feature code; s2, acquiring spatial features of the intelligent networked automobile based on a Q-learning algorithm; s3, obtaining the time characteristics of the intelligent connected automobile based on the LSTM network; s4, predicting the real-time track of the intelligent connected automobile through multi-feature fusion; and the real-time performance and the accuracy of vehicle track prediction are effectively improved.
本发明涉及智能网联汽车技术领域,尤其涉及一种基于改进神经网络的智能网联汽车实时轨迹预测方法,包括,步骤S1,对道路的交叉口的场景图进行建模并确定特征编码;步骤S2,基于Q‑learn ing算法获取智能网联汽车的空间特征;步骤S3基于LSTM网络获取智能网联汽车时间特征;步骤S4:多特征融合预测智能网联汽车的实时轨迹;有效提高了车辆轨迹预测的实时性和精确性。
Intelligent networked automobile real-time track prediction method based on improved neural network
基于改进神经网络的智能网联汽车实时轨迹预测方法
2023-12-29
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06T Bilddatenverarbeitung oder Bilddatenerzeugung allgemein , IMAGE DATA PROCESSING OR GENERATION, IN GENERAL |
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