This talk addresses four key issues in transportation data analytics; Unobserved heterogeneity, Data size, and prediction/causality trade-offs, Temporally shifting model parameters, and compensating behavior of users. A description and explanation of these issues are provided along with ideas as to how they might be addressed.
