FORECASTING THE INPUTS TO DYNAMIC MODEL SYSTEMS. IN: IN PERPETUAL MOTION: TRAVEL BEHAVIOR RESEARCH OPPORTUNITIES AND APPLICATION CHALLENGES

Travel behavior modeling is increasingly moving toward more disaggregate approaches using a variety of dynamic quantitative methods. In parallel, travel demand management, transportation system management, and intelligent transportation systems impact evaluation requires increased resolution in land use and strategy description that also calls for a move to finer disaggregate levels. This methodological movement from zonal to person-, household-, and site-based forecasting has amplified the need for finer detail in forecasts of social and economic circumstances of each person and/or household used in travel behavior equations. The premier tool used to provide modelers with such data is called sociodemographic microsimulation, promising potential for higher predictive power and flexibility when compared to other approaches. However, this approach provides only partial coverage in the data batteries needed by the newly developed dynamic travel demand systems and there remain many issues yet to be resolved. This chapter first gives examples of policies and associated new modeling frameworks followed by a list of emerging data needs. The data needs are presented in 3 groups (aggregate, disaggregate, and based on sociodemographic forecasting methods). The following section provides a discussion on data availability. The chapter concludes with a summary.