Abstract: This study presents a hierarchical trip distribution gravity model that can accommodate various spatial correlation structures. It is formulated on the basis of the solution to an equivalent optimization problem, and its parameters are estimated using a sequential maximum likelihood procedure. We conclude that accounting for spatial correlation through a hierarchical structure incorporated into gravity-type trip distribution models significantly increases their explanatory and predictive powers and improves the results they generate for use in transportation system planning processes.

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