The purpose of this literature review is to assess what is currently known about the ability of travel demand forecasting models (TDMs) to provide accurate forecasts for different types of transportation plans and projects with respect to different outcome measures of interest. The role of TDMs in assessing the implications of highway expansions for vehicle miles of travel (VMT) and greenhouse gas (GHG) emissions is of particular interest given the current regulatory context. Relevant studies for this review were found using a variety of search terms in the Transport Research International Documentation (TRID) database and Google Scholar. The report reviewed the available studies with respect to the themes of limitations of the models, validity testing and sensitivity testing, and VMT forecasting. 

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The goal of this project was to assess the capabilities of the travel demand forecasting models (TDMs) used by California’s metropolitan planning organizations (MPOs) with respect to forecasting the increase in vehicle miles of travel induced by highway capacity expansion. An expert panel assisted with the development of review questions to be used in assessing the models. These questions were used to assess each of the models currently used by the eighteen MPOs in California based on information found in readily available documents. The assessment found that seven MPOs are using activity-basedmodels, nine are using four-step, trip-based models, and two are using hybrid models. In general, the activity-based models do a better job of capturing possible induced travel effects. Only one model includes explicit feedback between the transportation system and land use patterns. The readily-available documentation of travel demand forecasting models in California is insufficient for fully understanding the variables included in each model component and the structure of feedbacks between components of the models.

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