Population Synthesis for Microsimulating Travel Behavior

Abstract

For the forecasting of activity-based travel demand, the representativeness of the base-year synthetic population is critical to the accuracy of subsequent simulation outcomes. To date, the conventional approach to synthesizing the base-year population has been based on the iterative proportional fitting procedure. Two issues associated with this conventional approach are discussed: the first is often termed as the zero-cell-value problem, and the second is related to the inability to control for statistical distributions of both household- and individual-level attributes. Then, a new population synthesis procedure is presented that addresses the limitations of the conventional approach. The new procedure is implemented into an operational software system and used to generate synthetic populations for the Dallas–Fort Worth area in Texas. Validation results indicate that the new procedure can produce a synthetic population that more closely represents the true population than the conventional approach can.