Travel Demand Models are the backbone decision-making for public transportation infrastructure investment, including for next generation connected and autonomous transportation systems. Yet, critiques of these models with respect to their usefulness for representing travel demand and needs of transport disadvantage communities are rare in the academic literature. With the objective of promoting travel demand models that are better equipped for assessing transportation impacts for underrepresented communities, this presentation highlights lessons learned from two case studies of applying travel demand analysis to understand the transportation accessibility of low income, elderly, and transit dependent communities. The case studies take place in two Michigan cities, Benton Harbor and Detroit. Overall, the case study findings show the importance of advancing data collection and curation approaches, as well as more carefully considering the ramifications of mis-specifying travel model structures, particularly for minority travel populations.
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