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METHOD OF PREDICTING TRAFFIC CONGESTION AND CONTROLLING TRAFFIC SIGNALS BASED ON DEEP LEARNING AND SERVER FOR PERFORMING THE SAME

  • US 20200135018A1
  • Filed: 11/12/2018
  • Published: 04/30/2020
  • Est. Priority Date: 10/24/2018
  • Status: Active Grant
First Claim
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1. A method of predicting traffic congestion and controlling traffic signals based on deep learning, the method being performed in a deep learning-based traffic congestion prediction and traffic signal control server, the method comprising:

  • analyzing regional network outflow behavior based on a per-intersection traffic demand pattern or traffic signal control, and determining a specific intersection to be a control target intersection based on results of the analysis;

    generating second-dimensional (2D) space-time images by analyzing data of predetermined customized composite data corresponding to the control target intersection and a plurality of pieces of image data for the control target intersection in terms of time and space;

    generating a real-time traffic congestion index by using the 2D space-time image of the control target intersection and the 2D space-time image of the data of the customized composite data corresponding to the control target intersection; and

    controlling traffic signals of the control target intersection based on the real-time traffic congestion index.

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