App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 8

Bus passenger flow prediction based on adaptive equilibrium static and dynamic joint network

Huang Lai'an
Zhu Hangxiong
Li Bo
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2023.12.0589

Abstract

To address the limitations of existing public transit passenger flow prediction methods, which often relied on predefined graph structures for spatial modeling, inadequately considered fluctuations in passenger flow caused by changes in traffic conditions, and failed to capture short-term dynamic spatial dependencies, this paper proposed an adaptively balanced static-dynamic joint network (ASDNet) model. Firstly, the model used a temporal convolution network to captured the temporal correlation of sequences. Secondly, it employed graph convolution to capture the overall spatial information between sites, and then incorporated a dynamic graph isomorphic network to capture the hidden dynamic dependencies between dynamic graphs of neighboring time slots. Finally, it introduced an adaptively balanced mechanism to adjust the information transfer between static-dynamic joint networks. The model tested a real bus dataset derived from Guangzhou City. The results demonstrated that the model reduced the MAE, RMSE, and MAPE prediction error metrics by an average of 12.2%, 9.9%, and 15%, respectively, and improved the R2 accuracy metrics by an average of 6.3% compared to several benchmark models. These results indicate that the model can effectively capture the spatiotemporal variation law of passenger flow data and provide technical reference for bus operation management.

Foundation Support

国家自然科学基金资助项目(62203123)
科技部外国专家项目(G2022030044L)
广州市科技计划项目(202206030005,202206010056)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.12.0589
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 8

Publish History

[2024-02-22] Accepted Paper

Cite This Article

黄来安, 朱杭雄, 栗波. 基于自适应平衡静动态联合网络的公交客流预测 [J]. 计算机应用研究, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.12.0589. (Huang Lai'an, Zhu Hangxiong, Li Bo. Bus passenger flow prediction based on adaptive equilibrium static and dynamic joint network [J]. Application Research of Computers, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.12.0589. )

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  • Application Research of Computers Monthly Journal
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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.

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