Special Topics in Multimodal Fusion
|
App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 12
3574-3581

Research on vehicle lane-changing intention prediction in expressway scenarios

Huang Haifeng
Huang Deqi
Huang Deyi
Liu Zhenhang
School of Electrical Engineering, Xinjiang University, Ürümqi 830017, China
DOI: 10.19734/j.issn.1001-3695.2025.05.0158

Abstract

Vehicle lane-changing behavior on highways in complex dynamic scenarios is highly prone to traffic accidents and affects road capacity. To improve the ability to predict lane-changing intentions, this study proposed a dual-channel GAT-MGCN model integrated with a self-attention mechanism for lane-changing intention recognition. The model combined highorder interaction features extracted by GATv2 with topological structure features captured by GCN through a learnable message-passing function, fusing them in high-dimensional space. Meanwhile, it employed linear projection to eliminate redundant information and a reconstruction mechanism to preserve critical features, significantly enhancing discriminative feature representation while optimizing model robustness and lightweight design. Through this joint feature representation, the model effectively integrated spatiotemporal interaction information from multi-source heterogeneous data, substantially improving the accuracy of lane-changing intention recognition. To address data imbalance, the study optimized the model using a dynamic loss function with class weights. Evaluations on the public HighD highway trajectory dataset demonstrate that the model outperforms traditional machine learning and existing deep learning methods in terms of accuracy, precision, and real-time performance. Ablation experiments further validate the key contributions of the proposed approach to model performance. This research provides a novel solution for predicting lane-changing intentions in highway scenarios.

Foundation Support

新疆维吾尔自治区自然科学基金资助项目(2022D01C430)
国家自然科学基金资助项目(51468062)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.05.0158
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 12
Section: Special Topics in Multimodal Fusion
Pages: 3574-3581
Serial Number: 1001-3695(2025)12-007-3574-08

Publish History

[2025-08-20] Accepted Paper
[2025-12-05] Printed Article

Cite This Article

黄海峰, 黄德启, 黄德意, 等. 高速公路场景下的车辆换道意图预测研究 [J]. 计算机应用研究, 2025, 42 (12): 3574-3581. (Huang Haifeng, Huang Deqi, Huang Deyi, et al. Research on vehicle lane-changing intention prediction in expressway scenarios [J]. Application Research of Computers, 2025, 42 (12): 3574-3581. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)