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Abstract
This paper examines the impact of travel demand modeling (TDM) disaggregation techniques in
the context of medium-sized communities. Specific TDM improvement strategies are evaluated for
predictive power and flexibility with case studies based on the Tyler, Texas, network. Results suggest
that adding time-of-day disaggregation, particularly in conjunction with multi-class assignment,
to a basic TDM framework has the most significant impacts on outputs. Other strategies shown to
impact outputs include adding a logit mode choice model and incorporating a congestion feedback
loop. For resource-constrained communities, these results show how model output and flexibility
vary for different settings and scenarios.