Spatial-temporal feature extraction and evaluation network for citywide traffic condition prediction

Traffic condition prediction is crucial for executing traffic control and scheduling tasks within intelligent transportation systems. With diversified data sources, effectively modeling the complex spatial-temporal dependencies in the whole traffic network and predicting nonlinear general traffic co...

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Bibliographic Details

Main Authors:	Liang Chu, Zhuoran Hou, Jingjing Jiang, Jun Yang, Yuanjian Zhang
Format:	Default Article
Published:	2023
Subjects:	Automotive engineering Control engineering, mechatronics and robotics Computer vision and multimedia computation traffic condition prediction deep learning graph convolution self-attention feature extraction
Online Access:	https://hdl.handle.net/2134/24316855.v1
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