基于时空图注意力网络的车辆多模态轨迹预测模型
|
陈文强,王东丹,朱文英,汪勇杰,王涛
|
Vehicle multimodal trajectory prediction model based on spatio-temporal graph attention network
|
Wenqiang CHEN,Dongdan WANG,Wenying ZHU,Yongjie WANG,Tao WANG
|
|
表 1 不同模型在5 s预测范围内的均方根误差 |
Tab.1 RMSE for different models in 5-second forecast range |
|
数据集 | RMSE | tf/s | S-LSTM[16] | CS-LSTM[15] | S-GAN[14] | PIP[18] | STDAN[17] | STGAMT(w/o IFE) | STGAMT | HighD | 1 | 0.22 | 0.22 | 0.20 | 0.17 | 0.19 | 0.07 | 0.07 | 2 | 0.62 | 0.61 | 0.57 | 0.52 | 0.27 | 0.19 | 0.19 | 3 | 1.27 | 1.24 | 1.14 | 1.05 | 0.48 | 0.35 | 0.32 | 4 | 2.15 | 2.10 | 1.90 | 1.76 | 0.91 | 0.65 | 0.61 | 5 | 3.14 | 3.27 | 2.91 | 2.63 | 1.66 | 1.20 | 1.14 | NGSIM | 1 | 0.65 | 0.61 | 0.57 | 0.55 | 0.42 | 0.22 | 0.21 | 2 | 1.31 | 1.27 | 1.32 | 1.18 | 1.01 | 0.80 | 0.78 | 3 | 2.16 | 2.09 | 2.22 | 1.94 | 1.69 | 1.52 | 1.49 | 4 | 3.25 | 3.10 | 3.26 | 2.88 | 2.56 | 2.47 | 2.40 | 5 | 4.55 | 4.37 | 4.40 | 4.04 | 3.67 | 3.69 | 3.58 |
|
|
|