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Data-Driven Traffic Reconstruction and Kernel Methods for Identifying Stop-and-Go Congestion
Identifying stop-and-go events (SAGs) in traffic flow presents an important avenue for advancing data-driven research for climate change mitigation and sustainability, owing to their substantial impact on carbon emissions, travel time, fuel consumption, and roadway safety.
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