AIMC Topic: Transportation

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T-RippleGNN: Predicting traffic flow through ripple propagation with attentive graph neural networks.

PloS one
Recently, accurate traffic flow prediction has become a significant part of intelligent transportation systems, which can not only satisfy citizens' travel need and life satisfaction, but also benefit urban traffic management and control. However, tr...

From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

Proceedings of the National Academy of Sciences of the United States of America
The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational dat...