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Vehicle Trajectory Prediction Method Based on Social GAN Network and Self-Attention Mechanism
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Langqian Zhu1, Shijun Ma1, Mingjian Liu1, 2, Muyang Li1, Changsheng Hao1
Automobile Technology | 2025, (6) : 8 - 14
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Automobile Technology | 2025, (6): 8-14
Vehicle Trajectory Prediction Method Based on Social GAN Network and Self-Attention Mechanism
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Langqian Zhu1, Shijun Ma1, Mingjian Liu1, 2, Muyang Li1, Changsheng Hao1
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  • 1 College of Information Engineering, Dalian Ocean University, Dalian 116023
  • 2 Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian Ocean University, Dalian 116023
Published: 2025-06-24 doi: 10.19620/j.cnki.1000-3703.20240867
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To address the issue that temporal features and spatial factors of the traffic environment affect the accuracy of vehicle trajectory prediction in vehicle driving, this paper proposes a vehicle trajectory prediction method integrating temporal multi-head self-attention and social pooling based on the Social Generative Adversarial Network (SMA-GAN). Firstly, the historical trajectory features are extracted by the temporal correlation of the target vehicle’s own trajectory data using the multi-head self-attention mechanism. Then, the spatial dimensional features of the target vehicle are extracted by the social pooling mechanism based on the spatial positional relationship between the target vehicle and the surrounding vehicles. Finally, the predicted trajectory of the target vehicle is obtained by the encoder-decoder. Model training and comparison tests are conducted using the NGSIM dataset, and the results show that the SMA-GAN model has higher prediction accuracy and efficiency in the highway scene.

Intelligent vehicle  /  Trajectory prediction  /  Generative Adversarial Network (GAN)  /  Social pooling mechanism  /  Self-attention mechanism
Langqian Zhu, Shijun Ma, Mingjian Liu, Muyang Li, Changsheng Hao. Vehicle Trajectory Prediction Method Based on Social GAN Network and Self-Attention Mechanism[J]. Automobile Technology, 2025 , (6) : 8 -14 . DOI: 10.19620/j.cnki.1000-3703.20240867
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doi: 10.19620/j.cnki.1000-3703.20240867
  • Online Date：2025-11-12
  • Published：2025-06-24
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  • Revised：2025-01-16
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    1 College of Information Engineering, Dalian Ocean University, Dalian 116023
    2 Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian Ocean University, Dalian 116023
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