Tired Of Rush Hour Traffic? A Machine Could Fix That

A deep reinforcement learning algorithm could optimally plan traffic signals and help to reduce congestion, according to a new study. Asian Scientist Newsroom | August 24, 2016 | Technology AsianScientist (Aug. 24, 2016) – A study from China published in the IEEE/CAA Journal of Automatica Sinica suggests that machines can learn how to plan traffic signals to reduce wait times and make traffic queues shorter. In traffic signaling, it’s the pattern of traffic light switches that minimizes the time drivers spend waiting in a queue or the length of that queue. Automating traffic control is notoriously tricky because it involves two challenging tasks: modeling traffic flow and then optimizing it. Much like the reward system in our brain, reinforcement learning algorithms operate by determining what set of actions are most…


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