Why are some morning commutes so much worse than others?

New research shows that nighttime and early-morning energy use can be a good predictor of morning traffic congestion.

Sean Qian, an assistant professor of civil and environmental engineering at Carnegie Mellon University, and Ph.D. student Pinchao Zhang created a model that mined data on electricity consumption from 322 homes in Austin, Texas, and used artificial intelligence to predict what traffic would look like the next morning.

The anonymous electricity data was collected by Pecan Street Inc., which had enrolled hundreds of homes in the Austin area in an advanced metering infrastructure, or smart meter, program that tracks energy consumption. Travel time data came from the National Performance Management Research Data Set.
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