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Machine Learning Techniques Aim to Reduce Traffic

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Sick of sitting in traffic? Deep reinforcement learning may be the answer.

It's a problem we can all relate to: sitting in traffic and waiting for a green light. While waiting, you may have even pondered how you would try to improve traffic efficiency—surely there's got to be some way for everyone to get to work on time.

But ponder no longer, because a team of engineers from Tsinghua University in China has handed the problem over to machines. The team’s recent study makes use of deep reinforcement learning algorithms to optimize traffic signaling, and its promising results suggest there may be a way to arrive on time after all.

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