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On the Design of Graph Embeddings for the Sensorless Estimation of Road Traffic Profiles. (arXiv:2201.04968v1 [cs.LG])
Jan. 14, 2022, 2:10 a.m. | Eric L. Manibardo, Ibai Laña, Esther Villar, Javier Del Ser
cs.LG updates on arXiv.org arxiv.org
Traffic forecasting models rely on data that needs to be sensed, processed,
and stored. This requires the deployment and maintenance of traffic sensing
infrastructure, often leading to unaffordable monetary costs. The lack of
sensed locations can be complemented with synthetic data simulations that
further lower the economical investment needed for traffic monitoring. One of
the most common data generative approaches consists of producing real-like
traffic patterns, according to data distributions from analogous roads. The
process of detecting roads with similar …
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