In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) has been redirecting to new domain since Jan. 1st, 2025.
See More
App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 12

Monocular 3d lane detection for intelligent driving in complex road scenarios

Lou Lua
Hu Zhenkuna
Wei Wenjiea
Shen Yia
Wei Hanbingb
a. School of Information Science & Engineering, b. School of Mechatronics & Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China
DOI: 10.19734/j.issn.1001-3695.2025.03.0148

Abstract

Lane detection is essential for perception and decision-making in intelligent vehicles. To address the challenge that existing methods struggle to balance detection accuracy and speed in complex traffic scenarios, this paper proposes an efficient monocular 3D lane detection method. The proposed method leverages dynamic deformable convolution to effectively capture the curved and elongated shape features of lanes. It employs multi-scale view transformations and feature aggregation to reduce feature loss and obtain lane position information at different levels. Furthermore, it introduces an auxiliary supervision strategy with residual connections to enhance the model's representation capability. Experimental results on 3D lane detection benchmarks show that the proposed method achieves an F1-Score of 98.6% on the synthetic Apollo 3D dataset, outperforming BEV-LaneDet and LATR by 1.7% and 1.8%, respectively. On the large-scale real-world OpenLane dataset, the method reached an F1-Score of 59.8%, which was 1.4% higher than BEV-LaneDet. The performance gains were particularly notable in uphill/downhill and curved road scenes, with improvements of 4.6% and 2.5%, respectively. Although the F1-Score was 2.1% lower than the Transformer-based LATR method, the method ran at 80.1 FPS, which was 5.7 times faster than LATR’s 14 FPS. These results demonstrate that the proposed method can improve the accuracy and robustness of 3D lane detection in complex scenes, and achieve a favorable balance between detection performance and running inference speed.

Foundation Support

国家自然科学基金资助项目(52172381)
重庆市自然科学基金资助项目(cstc2021jcyj-msxmX1121)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.03.0148
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 12

Publish History

[2025-08-06] Accepted Paper

Cite This Article

娄路, 胡振坤, 魏文洁, 等. 复杂道路场景下智能驾驶单目3D车道线检测 [J]. 计算机应用研究, 2025, 42 (12). (2025-08-06). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0148. (Lou Lu, Hu Zhenkun, Wei Wenjie, et al. Monocular 3d lane detection for intelligent driving in complex road scenarios [J]. Application Research of Computers, 2025, 42 (12). (2025-08-06). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0148. )

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)