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A real-time vehicle trajectory prediction method based on the fusion of spatio-temporal awareness graph and multi-scale dilated convolution | Synapse
March 3, 2026
A real-time vehicle trajectory prediction method based on the fusion of spatio-temporal awareness graph and multi-scale dilated convolution
XG
Xiang Gu
Nantong University
CG
Chenwen Gu
JW
Jing Wang
Fujian Normal University
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Puntos clave
The method significantly enhances vehicle trajectory prediction accuracy, potentially benefiting traffic management.
An average prediction improvement of 20% was noted when using a fusion of spatio-temporal awareness graphs and dilated convolution.
Analysis involves a real-time prediction method that integrates multiple scales for data fusion, improving response times.
Highlights may indicate better routing options for automated driving systems, enhancing overall safety and efficiency.
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Gu et al. (Tue,) studied this question.
synapsesocial.com/papers/69a76058c6e9836116a2d014
https://doi.org/https://doi.org/10.1007/s00530-025-02200-x