Minimizing and reducing traffic jams

Machine Learning Techniques Aim To Reduce Traffic. Putting Public Needs Before Private Consumption /. The Only Hope for Reducing Traffic.

Traffic jams can be a total headache. It is a big problem to solve and the engineers keep working on how to reduce it and increase its’ efficiency. Engineers face a lot of difficulties, because of the two challenging tasks: first step is to create a useful model of traffic flow, and then another one is to find any way to optimize it. The first easy way by reducing traffic jam was eight-line intersection with only red and green signal lights and only straight way to go through (no right, left turns, U-turns). Another way is to combine the reinforcement learning algorithms with deep learning algorithms. These two algorithms can reduces the time needed to find optimized solutions. Deep reinforcement learning may be the answer for traffic jams reduction.

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  • 2017 m.
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Minimizing and reducing traffic jams. (2017 m. Gegužės 03 d.). Peržiūrėta 2018 m. Gegužės 24 d. 22:14