Vehicle Trajectory Prediction Method Based on GRU and Transformer
In order to enhance the understanding of the dynamic environment of autonomous vehicles and to improve road driving safety,this article proposed a vehicle trajectory prediction STGTF model based on the Gated Recurrent Unit(GRU)and Transformer that used the GRU to extract the historical trajectory features of vehicles,and used a two-layer Multi-Headed Attention(MHA)mechanism to extract the spatio-temporal interaction features of vehicles,generating the predicted trajectories.The experimental results show that the Root-Mean-Square Error(RMSE)of the predicted results decrease by 7.3％on average,STGTF model has different degrees of improvement compared with other existing methods for both short-term prediction and long-term prediction,proving validity of this model.
万方数据
维普
