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51 dition, forecasts from the statewide model are used to validate process, these case studies differ remarkably in both their or supersede forecasts made from historical data using details and execution. Each state has customized the model BoxCox regression analysis. Outputs are also processed steps to match its own planning objectives. This chapter through STEAM (Surface Transportation Efficiency Analysis shows three distinct methods of modeling statewide passen- Model) from FHWA to obtain systemwide benefits. ger travel. However, there is more similarity in the freight models, particularly in basing the forecasts on commodity Major updates of Wisconsin's model are planned to occur movements. Ohio's model emphasizes how non-freight on a 6-year cycle to coincide with Wisconsin DOT's Six- commercial vehicles can be important to a forecast and Year Highway Improvement Program. might need special treatment apart from freight-carrying vehicles. DISCUSSION Furthermore, the five case studies show that statewide models are becoming large and complex. The models are in- The five case studies are representative of the newer gener- creasing the demand for high-quality secondary data, faster ation of statewide travel forecasting models. Except for their hardware and algorithms, better data visualization methods, philosophy in following a three- or four-step forecasting and greater expertise.