A framework to improve urban accessibility and environmental conditions in age-friendly cities using graph modeling and multi-objective optimization

The rapid growth of cities in recent decades has unleashed several challenges for urban planning, which have been exacerbated by their aging population. Among the most pressing problems in cities are those related to mobility and environmental quality, by which a global concern has flourished around enhancing pedestrian accessibility for both environmental and health-related reasons. To tackle this issue, this paper presents a new framework that combines multi-objective optimization with a graph model that aims to support urban planning and management to enhance age-friendly cities. The framework allows designing urban projects that improve accessibility and reduce noise and/or air pollution through the installation of urban elements (ramps and escalators, elevators, acoustic and vegetation panels), while considering the overall economic cost of the installation. To explore the trade-off between these objectives, we resort to multi-objective evolutionary algorithms, which permit to compute near Pareto-optimal interventions over the graph model of the urban area under study. We showcase the applicability of the proposed framework over two use cases in the city of Barcelona (Spain), both quantitatively and qualitatively. Results evince that the framework can help urban planners make informed decisions towards enhancing urban accessibility and the environmental quality of age-friendly cities.