Scientists use artificial intelligence to forecast large-scale traffic patterns more accurately

It's no secret that Los Angeles is notorious for its traffic jams, typically ranking first in studies of the nation's traffic hot spots. Estimates suggest that Angelinos spend an extra 120 hours a year stuck in them. While a nightmare for drivers, the L.A. transportation system does have its advantages if you're devising a new system to quickly predict and potentially redirect that traffic. Researchers from across the U.S. Department of Energy's (DOE) Argonne National Laboratory set out to do just that under the umbrella of a larger project on the design and planning of mobility systems led by collaborators at DOE's Lawrence Berkeley National Laboratory (LBNL). Using an artificial intelligence (AI) technique called machine learning, the team leveraged Argonne's supercomputers to digest traffic patterns from nearly a year's worth of data taken from 11,160 sensors along the large California highway system.