The new Quick Response Freight Manual (QRFM) was used to model truck traffic in Centre County, Pennsylvania, using Geographic Information System software. The QRFM methodology of truck traffic estimation follows the three-step process of trip generation, trip distribution, and traffic assignment. Trip generation was estimated by four classes of business employment and number of households and was aggregated to traffic analysis zones. Trip distribution employed a doubly constrained gravity model with travel time–based friction factors. User equilibrium was used for traffic assignment. Model calibration was performed by comaparing total vehicle miles traveled from model output with observed data. A comparison is made in truck traffic estimation between two models when the model resolution is changed, that is, when the size and number of traffic analysis zones (TAZs) is changed. One model uses census tracts and the other uses census blocks and block groups as TAZs. Both models use the same network, which includes all major highways and most local roads in the urbanized region of the county. Results from the two aggregation scales of analysis were compared with each other by using traffic counts in the Roadway Management System of Pennsylvania as reference data. The estimated truck traffic link volumes favor the use of the more disaggregate TAZ scheme, which is based on blocks and block groups.


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    Title :

    Truck Traffic Prediction Using Quick Response Freight Model Under Different Degrees of Geographic Resolution: Geographic Information System Application in Pennsylvania


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    1998-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Truck Traffic Prediction Using Quick Response Freight Model Under Different Degrees of Geographic Resolution: Geographic Information System Application in Pennsylvania

    Marker, J. T. / Goulias, K. G. / National Research Council; Transportation Research Board | British Library Conference Proceedings | 1998



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