Dynamic Pattern Matching Network for Traffic Prediction

Yanguo Huang (), Weilong Han, Yingmin Xie and Shuiqing Wu
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Yanguo Huang: School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China
Weilong Han: School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China
Yingmin Xie: School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China
Shuiqing Wu: Jiangxi Yongan Traffic Facilities Technology Co., Ltd., Ji’an 343009, China

Sustainability, 2025, vol. 17, issue 9, 1-17

Abstract: Due to the inherent complexity of urban road networks and the irregular periodic fluctuations of traffic flow, traffic forecasting remains a challenging spatiotemporal modeling task.Existing studies predominantly focus on capturing spatial dependencies among nodes, while often overlooking the long-term evolutionary patterns and internally stable, recurring flow behaviors at individual nodes. This limitation compromises both the generalization capacity and long-term forecasting performance of current models.To address these issues, we propose a novel Dynamic Pattern Matching Network (DPMNet) that incorporates a memory-augmented architecture to dynamically learn and retrieve historical traffic patterns at each node, thereby enabling efficient modeling of localized flow dynamics. Building upon this foundation, we further develop a comprehensive framework named DPMformer, which integrates daily and weekly temporal embeddings to enhance the modeling of long-term trends and leverages a pattern matching mechanism to improve the representation of complex spatiotemporal structures.Extensive experiments conducted on four real-world traffic datasets demonstrate that the proposed method significantly outperforms mainstream baseline models across multiple forecasting horizons and evaluation metrics.

Keywords: traffic prediction; pattern matching; memory network; time embedding (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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