The increased use of equipment having automatic vehicle classification capabilities and weigh-in-motion devices produces a large amount of new data that can provide some insights into understanding traffic patterns more efficiently. These data can be used in determining seasonal adjustment factors for correcting traffic counts, in estimating truck traffic for highway cost allocation studies, and in predicting traffic volumes for roadways. However, due to practical limitations, it is not possible to obtain continuous data collection for all roads; thus, short-term counts are usually performed. Therefore, it is important to understand the relationship of the data obtained in a short-term period to those for the entire year. A study is currently under way that determines these relationships and develops seasonal adjustment factors for the state of Kentucky. The first step of the study was a survey of current uses of vehicle classification data and methods used for data collection throughout the United States. The results indicated that most states use no seasonal adjustment factors nor are they planning to develop any factors in the near future. At the same time, analysis of 2 years of vehicle classification data was used to develop seasonal and daily factors for Kentucky. Currently, the validation of these factors is under way. The preliminary analysis indicated that seasonal adjustment factors are essential in developing accurate estimates of traffic volumes for each vehicle type, and their use can improve the estimation of daily volumes.


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    Titel :

    Seasonal Factors Using Vehicle Classification Data


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    01.01.1997




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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