Data Structures for Transportation Equity Analysis

Explore data structures for transportation equity analysis in this 47-minute conference talk presented by Joseph Chow of New York University at IPAM's Mathematical Foundations for Equity in Transportation Systems Workshop. Delve into the importance of adequate data representation for quantifying population differences and learn about algorithms designed to address the Modifiable Areal Unit Problem, ensuring fairer representations of diverse population segments. Examine the use of population synthesis and discover aggregate mode choice models that capture taste heterogeneity at the Census block group level. Gain insights into integrating these models with mobility service optimization for choice-based minimization of income disparity in resource allocation. Discuss policy implications and understand how these data structures and methodologies contribute to more equitable transportation systems analysis.

Joseph Chow - Data structures for transportation equity analysis - IPAM at UCLA