In the blog post, Google and DeepMind researchers explain how they take data from various sources and feed it into machine learning models to predict traffic flows. This data includes live traffic information collected anonymously from Android devices, historical traffic data, information like speed limits and construction sites from local governments, and also factors like the quality, size, and direction of any given road. So, in Google’s estimates, paved roads beat unpaved ones, while the algorithm will decide it’s sometimes faster to take a longer stretch of motorway than navigate multiple winding streets.
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