Estimation of discrete choice models requires information on the alternatives available to individual travelers and the choices those travelers make in response to the characteristics of the alternatives available. Estimation datasets for many discrete choice models (e.g. mode choice and destination choice models) used in trip-based models (TBMs) and activity-based models (ABMs) are constructed by posting modeled auto and transit skim information on survey data for individual travelers. Good model development and model validation practice dictate that the roadway and transit networks and network skimming processes be validated prior to the marrying of the skim data with the choice data.

The Travel Model Validation and Reasonableness Checking Manual – Second Edition suggests several aggregate checks for auto and transit skims. The checks focus on frequency distributions of the variables for the mode alternatives used in the modeling process – in-vehicle travel times, distances, costs, implied interchange speeds, numbers of transfers, out-of-vehicle times, etc. While such tests are important, they do not provide information regarding the veracity of modeled interchange travel impedances with the alternatives actually faced by the individual travelers.

This presentation reports on three alternative techniques for validation of networks and skims:

• First is the use of prediction-success tables to compare modeled to reported transit boardings for individual travelers. While this technique has been used elsewhere, it was refined for a TBM development process for the Southeast Michigan Council of Governments (SEMCOG). Specifically, better techniques were developed for analyzing modeled boardings reported by a transit multipath path-builder.

• Second is a disaggregate validation test of the auto skims used for the Houston-Galveston Area Council (H-GAC) ABM development project. While the auto test was not used to adjust path-building parameters, it was used to identify outliers in the estimation dataset so they could be removed from model estimations that could be negatively impacted by their use.

• Third is the validation of transit networks in the Minneapolis-St. Paul region through the comparison of modeled route profiles from a transit assignment of an expanded on-board survey to observed route profiles developed from transit boarding and alighting counts.