The invention discloses a neural network vehicle trajectory prediction method based on a self-attention mechanism. The neural network vehicle trajectory prediction method comprises the steps of 1, collecting vehicle historical trajectory information, a relative distance between a vehicle and a target vehicle in a target lane and a relative speed between the vehicle and the target vehicle in the target lane; step 2, constructing a neural network based on a self-attention mechanism, and inputting the parameters obtained in the step 1 into the neural network to obtain a predicted trajectory of the vehicle; the encoder comprises a second input layer, a first embedded layer, a first multi-head probability sparse self-attention module, a first feed-forward layer, a first self-attention distillation module, a second multi-head probability sparse self-attention module, a second embedded layer and a first output layer, and the output of the first output layer is the lane changing state of the vehicle. The method has the characteristic of improving the prediction accuracy and applicability.
本发明公开了一种基于自注意力机制的神经网络车辆轨迹预测方法,包括:步骤一、采集车辆历史轨迹信息、本车与目标车道中目标车辆之间相对距离和本车与目标车道中目标车辆之间的相对速度;步骤二、构建基于自注意力机制的神经网络,并将步骤一种获得参数输入神经网络中,获得车辆的预测轨迹;所述编码器包括第二输入层、第一嵌入层、第一多头概率稀疏自注意力模块、第一前馈层、第一自注意力蒸馏模块、第二多头概率稀疏自注意力模块、第二嵌入层和第一输出层,所述第一输出层的输出为本车的换道状态。本发明具有提高预测准确性和适用性的特点。
Neural network vehicle trajectory prediction method based on self-attention mechanism
一种基于自注意力机制的神经网络车辆轨迹预测方法
2025-05-27
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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