Accessibility, Equity, and Safety in Emerging Mid-Sized Cities: An AI-Based Assessment of Future BRT Corridors in Querétaro, Mexico

Emerging mid-sized cities in the Global South face growing challenges in aligning transport infrastructure with equity and safety objectives under conditions of rapid urban expansion. While accessibility metrics are widely used in transport planning, their ability to capture functional inequalities and safety-related dynamics remains limited, particularly in corridor-level assessments. This study examines structural and functional accessibility patterns along two planned BRT corridors in Querétaro, Mexico, an emerging mid-sized Latin American city. The analysis integrates spatial accessibility indicators, selected urban process proxies related to inequality and road safety, and AI-based modeling to explore non-linear spatial associations across fine-grained corridor segments. Structural accessibility is evaluated using network-based indicators, while functional accessibility reflects observed service dynamics and operational conditions. Spatial correlations and artificial neural networks are employed as exploratory tools to identify co-occurring patterns rather than causal relationships. Results reveal pronounced spatial mismatches between structural and functional accessibility, socio-spatial marginalization, and crash concentration, highlighting corridor segments where future BRT implementation may either reinforce or mitigate existing inequalities. By framing BRT corridors as test cases, the study contributes a transferable diagnostic framework for assessing accessibility–equity–safety tensions in emerging mid-sized cities.