United States Department of Transportation
i
NY Statewide Behavioral Equity Impact Decision Support Tool with Replica
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2023-07-01
[PDF-4.89 MB]
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Edition:Final Report
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Abstract:A NY statewide model choice model is developed to deterministically fit heterogeneous coefficients for trips along each census block-group OD pair conducted by each population segment within a random-utility-consistent framework. The proposed approach is to use inverse optimization (IO) to derive coefficients for each OD pair times population segment as an agent. This is only possible with ubiquitous population data. We call this a group-level agent-based mixed logit (g-AMXL) model, which is an extension of the AMXL model proposed by Ren and Chow (2022). The significance of g-AMXL is as follows. First, g-AMXL takes OD level (instead of individual level) trip data as inputs, which is efficient in dealing with ubiquitous datasets containing millions of observations. Second, preference heterogeneities are based on non-parametric aggregation of coefficients per agent instead of having to assume a distributional fit. Third, since each agent’s representative utility function is fully specified, g-AMXL can be directly integrated into system design optimization models as constraints instead of dealing with simulation-based approaches required by mixed logit (MXL) models.
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