Transformer-based short-term traffic forecasting model considering traffic spatiotemporal correlation
Traffic forecasting is crucial for a variety of applications, including route optimization, signal management, and travel time estimation. However, many existing prediction models struggle to accurately capture the spatiotemporal patterns in traffic data due to its inherent nonlinearity, high dimens...
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Main Authors: | Ande Chang, Yuting Ji, Yiming Bie |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-01-01
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Series: | Frontiers in Neurorobotics |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fnbot.2025.1527908/full |
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