App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 6

Online prediction method for traffic flow on expressways integrating time-space characteristic

Zou Fumin1
Ma Jiyuan1
Cai Qiqin2
1. Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350118, China
2. Zhangzhou Institute of Technology, Zhangzhou Fujian 363099, China
DOI: 10.19734/j.issn.1001-3695.2025.09.0432

Abstract

To address the limitations of existing models in expressway short-term traffic flow forecasting, including insufficient online updating capability, high computational complexity, and restricted real-time performance, an online prediction model named ARMA_ONS–ORELM was developed. The model employs ARMA_ONS to perform adaptive online modeling of segment-level traffic flow series and extract dynamic periodic features. These features are further integrated with upstream and downstream spatial adjacency features derived from gantry topology and distance-weighted relationships, forming unified spatiotemporal inputs. A multi-step recursive Online Extreme Learning Machine (ORELM) is then used to generate online predictions of 15-minute in-transit traffic volumes. Experiments on real ETC gantry transaction data show that the model outperforms multiple baseline approaches, achieving an R² of 0.978, MAE of 8.19, RMSE of 10.88, and MSE of 118.34. The results indicate that the framework maintains millisecond-level update efficiency while preserving prediction accuracy, providing an effective and lightweight solution for real-time expressway traffic flow prediction.

Foundation Support

科研启协基金项目:交通轨迹数据的城市交通需求时空分布与演化模式挖掘(GY-Z24043)
福建省青年科技人员育成项目(2025350443)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.09.0432
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 6

Publish History

[2026-02-26] Accepted Paper

Cite This Article

邹复民, 马纪媛, 蔡祈钦. 融合时空特征的高速公路在途车流量在线预测方法 [J]. 计算机应用研究, 2026, 43 (6). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0432. (Zou Fumin, Ma Jiyuan, Cai Qiqin. Online prediction method for traffic flow on expressways integrating time-space characteristic [J]. Application Research of Computers, 2026, 43 (6). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0432. )

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.

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