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In practice, destination choice models can rarely be applied for forecasting exactly as they are estimated. Calibration adjustments are commonly required for several reasons. Sometimes application of the model to application data sets produce results that differ in some important ways from the results when the model is applied to the estimation data sets. In some cases such differences can be caused or exacerbated by inconsistencies between the model estimation and application (such as different sources for explanatory variables like income or travel time or the omission of constraints in estimation). Careful and thoughtful adjustments in keeping with good professional judgment can be required in order ensure the applied model demonstrates both reasonable ability to replicate observed travel patterns (from both estimation data and in some cases, other independent data sources for validation) and reasonable response properties or elasticities to key variables.

Calibration Measures

A variety of measures can be used to evaluate the validity of destination choice models. Comparisons to trip length frequency distributions remain the most common approaches although it has been demonstrated that models can easily be over-calibrated to reproduce trip length frequency distributions at the expense of their ability to accurately reproduce actual spatial interaction patterns.[1]


Calibration Strategies

Various strategies can be and are commonly employed such as adjustments to distance or impedance parameters, the assertion of size or mode choice logsum parameters, and the use of constants.

References

Content Charrette: Destination Choice Models

  1. Ye, X., W. Cheng and X. Jia (2012) "Synthetic Environment to Evaluate Alternative Trip Distribution Models." Transportation Research Record: Journal of the Transportation Research Board, No. 2302: p. 111-120.