Urban intersection traffic flow prediction: A physics-guided stepwise framework utilizing spatio-temporal graph neural network algorithms

Urban intersection traffic flow prediction: A physics-guided stepwise framework utilizing spatio-temporal graph neural network algorithms

Accurate traffic flow forecasting at urban intersections is critical for optimizing transportation infrastructure and reducing congestion. This manuscript introduces a novel framework, the Physics-Guided Spatio-Temporal Graph Neural Network (PG-STGNN), specifically designed for traffic flow predicti...

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Bibliographic Details
Main Authors: Yuyan Annie Pan, Fuliang Li, Anran Li, Zhiqiang Niu, Zhen Liu
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Multimodal Transportation
Subjects:
Urban transportation planning
Traffic flow prediction
Physics-guided spatio-temporal graph neural network (PG-STGNN)
Long Short-Term Memory (LSTM)
Online Access:http://www.sciencedirect.com/science/article/pii/S2772586325000218
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