The invention discloses a driving track prediction method and device, a terminal and a storage medium, and belongs to the technical field of vehicles. The method comprises the following steps of: acquiring driving data of a target vehicle in a first time period, and acquiring driving data of a plurality of first vehicles in the first time period, inputting the driving data of the target vehicle inthe first time period and the driving data of the plurality of first vehicles in the first time period into a time sequence convolution network, and predicting a driving track of the target vehicle in a second time period through the time sequence convolution network. The driving data of the target vehicle and the plurality of first vehicles in the first time period are collected and input into the time sequence convolution network, and the driving track of the target vehicle in the second time period is predicted. The time sequence convolution network is a neural network for predicting the time sequence, and the network structure of the time sequence convolution network enables the output to contain more input features, so that the accuracy of time sequence prediction can be improved, and the driving track of the target vehicle can be accurately predicted.
本申请公开了一种行驶轨迹预测方法、装置、终端及存储介质,属于车辆技术领域。所述方法包括:采集目标车辆在第一时间段内的行驶数据,获取多台第一车辆在第一时间段内的行驶数据,将目标车辆在第一时间段内的行驶数据、多台第一车辆在第一时间段内的行驶数据输入时序卷积网络,通过时序卷积网络预测目标车辆在第二时间段内的行驶轨迹。通过采集目标车辆和多台第一车辆在第一时间段内的行驶数据,将其输入时序卷积网络,预测目标车辆在第二时间段内的行驶轨迹。时序卷积网络是对时间序列预测的神经网络,时序卷积网络的网络结构使输出包含有较多的输入特征,能够提高对时间序列预测的精确性,能够对目标车辆的行驶轨迹做出精确的预测。
Driving track prediction method and device, terminal and storage medium
行驶轨迹预测方法、装置、终端及存储介质
2020-05-08
Patent
Electronic Resource
Chinese
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 |
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