Unveiling travel communities of people with disabilities using smart card data: A case study of Nanjing

Abstract

Mobility barriers for people with disabilities remain a critical issue in many cities, especially in developing countries. This study uses metro smart card data from Nanjing, China, to explore the spatiotemporal patterns and network-based community structures of metro travel among disabled individuals. Results show a distinct “dual-peak” travel pattern and a “core-periphery” spatial structure, with higher network centrality during peak hours. Community detection reveals four types of travel clusters—commuting-oriented, residence-dominated, mixed-function, and special-node—each shaped by both travel purpose and urban functions. Spatial regression analysis highlights transit accessibility and land-use mix as key factors influencing travel flow. These findings offer insights for promoting transport equity and optimizing accessible transit planning.