Abstract The qualitative collection of traffic information is an important task. It allows to make adequate decisions at the design stage, reconstruction, repair of roads, and also helps to manage traffic. The quality of traffic control systems depends on the accuracy of determining parameters of traffic flow. The main parameter is intensity. In this article proposed to consider the problem of determining the intensity not as a problem of the classification of objects, but as a problem of segmentation. A software implementation of a method for determining the intensity of traffic, which based on a neural network and analysis of information from video cameras of traffic monitoring, has been developed. The neural network was trained on data that was obtained using the method of motion detection. It is proposed to use the TLCR (Traffic lane congestion ratio) parameter instead of AADT (Average Annual Daily Traffic) for more accurate transmission of information about the current traffic situation.


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    Title :

    Traffic Lane Congestion Ratio Evaluation by Video Data


    Contributors:


    Publication date :

    2019-07-18


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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