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Research on Expressway Congestion Warning Technology Based on YOLOv11-DIoU and GRU-Attention

arXiv — cs.CV•Wednesday, November 5, 2025 at 5:00:00 AM
PositiveArtificial Intelligence

Research on Expressway Congestion Warning Technology Based on YOLOv11-DIoU and GRU-Attention

A recent study published on arXiv presents a novel framework designed to address expressway traffic congestion, a significant factor that reduces travel efficiency. The research focuses on enhancing vehicle perception accuracy and improving congestion forecasting by optimizing the YOLOv11 algorithm and integrating it with a GRU-Attention mechanism. This combined approach aims to overcome limitations in current detection and prediction systems used for traffic management. By leveraging these advanced algorithms, the framework seeks to provide more accurate and timely warnings about congestion on expressways. The study highlights the potential effectiveness of this method in mitigating traffic delays and improving overall road usage. This work aligns with ongoing efforts in the field to apply artificial intelligence techniques to real-world transportation challenges. It contributes to the broader discourse on how AI can support smarter, more responsive traffic systems.

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