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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 8

Vehicles trajectory prediction approach based on Transformer with edge update and multi-head attention interactive fusion

Sun Yinga
Wu Yanyongb
Ding Deruib
Zhang Jiankunb
a. Business School, b. School of Optical-Electrical & Computer Engineering, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2025.01.0017

Abstract

The task of vehicle trajectory prediction for autonomous driving needs to fully consider the relationship between the traffic agents and the environment. Addressing the limitations of existing approaches at the level of heterogeneous feature interaction and improving prediction accuracy, the paper proposed a vehicle trajectory prediction approach named EMATNet(Edge-based Multi-head Attention Interactive Fusion Transformer Network) with edge updating and multi-head attention interactive fusion Transformer. First, the approach encoded and embedded the historical spatio-temporal information of the agents and the transportation environment. Then, the approach used the proposed two-stage interaction network of edge updating and multi-attention interaction fusion Transformer for feature interaction. The introduced symmetric positional embedding and vehicle-road relationship interaction could effectively enhance the global information perception and spatio-temporal relationship capturing capability. Finally, this approach used two-stage optimization decoding to ensure the accuracy and reasonableness of the prediction results. The proposed approach validates on Argoverse1 and Argoverse2 motion prediction datasets, and visualizes and analyzes the prediction results. The results show that EMATNet outperforms similar approches in the three performance metrics of minFDE, minADE and MR, and is capable for the task of vehicle trajectory prediction in complex traffic environments.

Foundation Support

国家自然科学基金资助项目(62203306,62373251)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.01.0017
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 8

Publish History

[2025-04-07] Accepted Paper

Cite This Article

孙颖, 吴延勇, 丁德锐, 等. 基于边更新与多头交互融合Transformer的车辆轨迹预测方法 [J]. 计算机应用研究, 2025, 42 (8). (2025-04-17). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0017. (Sun Ying, Wu Yanyong, Ding Derui, et al. Vehicles trajectory prediction approach based on Transformer with edge update and multi-head attention interactive fusion [J]. Application Research of Computers, 2025, 42 (8). (2025-04-17). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0017. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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