🤖 AI Summary
This study identifies a tripartite inequity in San Diego’s multimodal transportation system: (1) a core–periphery structural disconnection; (2) a transit accessibility gap—30.3% of points of interest lack bus coverage within walking distance; and (3) excessive highway dependence, resulting in low overall walkability, especially in suburban and rural areas. To address this, we construct an integrated multilayer network incorporating driving, walking, and public transit, fusing OpenStreetMap and Metropolitan Transit System data. We propose a novel walkability metric grounded in path connectivity and service radius, and conduct comprehensive diagnostics via centrality analysis, community detection, and multiscale accessibility assessment. Results show that travel-scale characteristics are governed by the dominant transport mode, while system resilience is disproportionately determined by critical highway nodes. The framework delivers a transferable methodology for assessing transportation equity and resilience in urban contexts.
📝 Abstract
Analyzing the structure and function of urban transportation networks is critical for enhancing mobility, equity, and resilience. This paper leverages network science to conduct a multi-modal analysis of San Diego's transportation system. We construct a multi-layer graph using data from OpenStreetMap (OSM) and the San Diego Metropolitan Transit System (MTS), representing driving, walking, and public transit layers. By integrating thousands of Points of Interest (POIs), we analyze network accessibility, structure, and resilience through centrality measures, community detection, and a proposed metric for walkability.
Our analysis reveals a system defined by a stark core-periphery divide. We find that while the urban core is well-integrated, 30.3% of POIs are isolated from public transit within a walkable distance, indicating significant equity gaps in suburban and rural access. Centrality analysis highlights the driving network's over-reliance on critical freeways as bottlenecks, suggesting low network resilience, while confirming that San Diego is not a broadly walkable city. Furthermore, community detection demonstrates that transportation mode dictates the scale of mobility, producing compact, local clusters for walking and broad, regional clusters for driving. Collectively, this work provides a comprehensive framework for diagnosing urban mobility systems, offering quantitative insights that can inform targeted interventions to improve transportation equity and infrastructure resilience in San Diego.