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Vehicle Trajectory Prediction Method Based on GRU and Transformer
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Qingrong Wang1, Xiaoze Tan1, Changfeng Zhu2, Yujie Li1
Automobile Technology | 2024, (7) : 1 - 8
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Automobile Technology | 2024, (7): 1-8
• Feature Topic on Motion Planning and Control Techniques •
Vehicle Trajectory Prediction Method Based on GRU and Transformer
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Qingrong Wang1, Xiaoze Tan1, Changfeng Zhu2, Yujie Li1
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  • 1 Institute of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070
  • 2 Institute of Transportation, Lanzhou Jiaotong University, Lanzhou 730070
Published: 2024-07-24 doi: 10.19620/j.cnki.1000-3703.20230877
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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.

Vehicle trajectory prediction  /  Gated Recurrent Unit (GRU)  /  Transformer  /  Vehicle interaction  /  Multi-head attention mechanism
Qingrong Wang, Xiaoze Tan, Changfeng Zhu, Yujie Li. Vehicle Trajectory Prediction Method Based on GRU and Transformer[J]. Automobile Technology, 2024 , (7) : 1 -8 . DOI: 10.19620/j.cnki.1000-3703.20230877
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doi: 10.19620/j.cnki.1000-3703.20230877
  • Online Date：2025-12-22
  • Published：2024-07-24
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    1 Institute of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070
    2 Institute of Transportation, Lanzhou Jiaotong University, Lanzhou 730070
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