Population Synthesis for Microsimulating Travel Behavior
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For the purpose of activity-based travel demand forecasting, the representativeness of the base year synthetic population is critical to the accuracy of subsequent simulation outcomes. To date, the conventional approach for synthesizing the base year population is based on the methodology first developed by Beckman et al. (1996). In this paper, we discuss two issues associated with this conventional approach. The first issue is often termed as the zero-cell-value problem, and the second issue is related to the inability to control for statistical distributions of both household and individual-level attributes. We then present a new population synthesis procedure that addresses the limitations of the conventional approach. The new procedure is implemented into an operational software system and is used to generate synthetic populations for the Dallas/Fort-Worth area in Texas. Our validation results show that, compared to the conventional approach, the new procedure produces a synthetic population that more closely represents the true population.
At the time of publication J.Y. Guo was at the University of Wisconsin-Madison; and C.R. Bhat was at the University of Texas at Austin.