Synthetic Environment to Evaluate Alternative Trip Distribution Models

Abstract

In this paper an environment is synthesized to incorporate spatial distributions of population and employees and to simulate travelers’ destination choice behaviors following utility-maximization decision rules. In this synthetic environment, two alternative trip distribution models—the destination choice model and the gravity model—are evaluated by comparing estimated model coefficients and trip matrices against their true counterparts. The destination choice model provides reasonable model coefficients and trip matrix when the average trip length is much greater than the zone size. However, when the average trip length comes closer to the zone size as a result of significant spatial aggregation errors the model coefficients appear more biased, and more errors occur in trip matrix estimation. In the gravity model, linear regression does not provide consistent coefficients for trip attraction variables and therefore cannot accurately estimate trip attractions. It is not optional but necessary to apply the destination choice model for consistently estimating the trip attraction and trip matrix in trip distribution.

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