This analysis examines non-linear impacts of built environment on OD flow in metro systems, suggesting critical insights for urban development.
Origin–destination (OD) passenger flow is a critical variable for metro system planning and operation. While numerous studies have investigated the influence of the built environment on passenger flow, most have focused on ingress or egress flows at metro stations. The impact of the built environment on OD flow dynamics, particularly the differences between origin-side and destination-side effects, remains poorly understood. This study proposes a novel method for exploring the non-linear effects of station-area built environments on OD flow in large-scale metro networks. First, hourly OD flows and station-area built environment features were extracted from multi-source data. Next, an analytical framework was developed to model the built environment–OD flow relationship using a gradient boosting decision tree model. Finally, the contributions of built environment variables and their non-linear effects on OD flows were systematically investigated. The proposed method was implemented on the Suzhou metro network in China. Test results show that most built environment variables exhibit time-varying, non-linear correlations with OD flows. Even the same variable demonstrates notable differences in its effect between the origin and destination sides. The findings of this study provide valuable guidance for metro planning and station-area urban development.
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Rao et al. (2025) studied this question.
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