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The objective of this study was to develop models which would simulate internal-external trips and external-external (through) trips. Regression analysis and cross-classification of data were tested in an attempt to predict the number of internal-external trips and the percentage of through trips. Regression analysis was used in the development of a through-trip distribution model. Grouping data for analysis created some problems; however, trial-and-error evaluation enabled selection of variables which produced reasonable results. Variables found to be most significant in the development of internal-external models were population and employment. For through-trip models, variables used were population, functional classification, AADT at the external station, and percent trucks. In developing through-trip distribution models, variables of significance were AADT at the destination station, percent trucks at destination station, percent through trips at destination station, and ratio of destination AADT to total AADT's at all stations (value squared). Overall, the models developed in this study appear to be adequate for planning purposes when ease of application and accuracy of the models are considered.
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