The objectives of the study were to develop a predictive algorithm for freeway congestion and to investigate and evaluate the current TSMC definition of freeway congestion or 'bottleneck' conditions. Data were collected along a section of the I-5 mainline northbound beginning at Downtown Station 108 and ending at Montlake Terrace Station 193 using two approaches: (1) time series modeling, and (2) pattern recognition. A pattern recognition approach was used to identify the best criteria for 'bottleneck' definition and also to identify the best criteria for predicting 'bottleneck' conditions. The time period for collection was 2:30 to 6:30 p.m. with a data time interval of 20 seconds.


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    Title :

    Freeway Congestion Prediction


    Contributors:
    N. L. Nihan (author)

    Publication date :

    1995


    Size :

    88 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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