Public transport vs. private vehicles: Spatial heterogeneity of accessibility to urban centers

Urban transportation systems critically influence energy consumption and carbon emissions. To evaluate urban accessibility, it is essential to systematically compare the spatiotemporal efficiency of public transport and private vehicles. However, traditional methods are limited by data acquisition and computation costs. This study proposes a novel, cost-effective framework using open-source map data and Python-based routing tools to compare the spatiotemporal efficiency of public transport and private vehicles. Utilizing real-time traffic data, we establish automated processing workflows to analyze spatial heterogeneity in accessibility across central urban areas of Nanjing, with comparisons to Shanghai and Hangzhou. Key findings include: (1) Taking Nanjing as a case study, the research evaluates public transport accessibility in eastern China's riverfront economic zone using key indicators like travel time ratios, advantage areas, and walking transfer time. Spatial differentiation maps were used to clearly delineate underdeveloped public transport areas in Nanjing; (2) Despite differences in urban form and structure, all three cities exhibit similar characteristics: comparable travel time ratios, concentration of public transport advantages within 10 km of the city center, and a notably high share of walking transfer time; (3) The framework provides a scalable tool for analyzing spatial accessibility heterogeneity, supporting evidence-based public transport policy development.