METHOD OF PREDICTING TRAFFIC CONGESTION AND CONTROLLING TRAFFIC SIGNALS BASED ON DEEP LEARNING AND SERVER FOR PERFORMING THE SAME
First Claim
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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Abstract
A method of predicting traffic congestion and controlling traffic signals based on deep learning according to an embodiment of the present invention includes: 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 the results of the analysis; generating 2D space-time images by analyzing the 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 the traffic signals of the control target intersection based on the real-time traffic congestion index.
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Citations
8 Claims
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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:
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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. - View Dependent Claims (2, 3, 4)
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5. A deep learning-based traffic congestion prediction and traffic signal control server, comprising:
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a control target intersection determination unit configured to analyze regional network outflow behavior based on a per-intersection traffic demand pattern or traffic signal control, and to determine a specific intersection to be a control target intersection based on results of the analysis; a 2D space-time image generation unit configured to generate 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; a real-time traffic congestion index generation unit configured to generate 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 a traffic signal control unit configured to control traffic signals of the control target intersection based on the real-time traffic congestion index. - View Dependent Claims (6, 7, 8)
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Specification