This study aims to develop a multi-objective optimization modeling framework to maximize the total accessibility to multi-use paths while minimizing the gap between low- and high- accessibility neighborhoods by an optimal allocation of active transportation investments for Fresno, California. Accessibility to multi-use paths is calculated for Fresno, California that measures the total length of multi-use paths (walkway and bikeway) a resident could reach to from the own block group with a 30-minute cycling ride. A geographically weighted regression (GWR) model is used to capture the local relationships between accessibility to multi-use paths and previous transportation investments (walkway, bikeway, and primary and secondary roads), while controlling for other socioeconomic factors. The marginal-effect analysis for the GWR results indicates economically efficient, inefficient, and indifferent locations for further investments. The GWR results are embedded into a multi-objective optimization modeling framework to improve accessibility to multi-use paths over the city and simultaneously address inequality in active-transportation accessibility. The methodology of this multi-objective optimization modeling provides decision makers a new insight into the problem of making of an economically-efficient and socially-equal active transportation plan to foster public health.
Principal Investigator:
PI Contact Information:
cwang@csufresno.edu
California State University, Fresno
