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https://doi.org/10.62836/iaet.v5i1.0001
Dai, W. (2026). Minimal Intervention, Maximum Throughput: Micro-Scale Optimization of Urban Rail Hubs. Innovations in Applied Engineering and Technology, 5(1), 0001. https://doi.org/10.62836/iaet.v5i1.0001
Volume 5, Issue 1, 2026

Minimal Intervention, Maximum Throughput: Micro-Scale Optimization of Urban Rail Hubs

The global stock of operational urban rail hubs faces a performance challenge: designed under earlier demand assumptions, many now exhibit severe transfer bottlenecks, fragmented pedestrian connectivity, and poorly resolved station-city interfaces. Conventional responses—structural reconfiguration and large-scale reconstruction—are increasingly constrained by fiscal austerity and spatial fixity in dense built-up areas. This paper addresses the absence of a systematic framework for micro-scale optimization of existing hubs under such constraints. A Diagnosis–Optimization–Evaluation framework is proposed, operationalized through the Station-City Minimal Intervention Maturity Model (SC-MIMM), integrating three-dimensional spatial conflict detection, quantifiable intervention thresholds, demand-based facility allocation, and closed-loop implementation verification. The framework is tested through a case study of a constrained interchange hub in a large Asian metropolitan rail network. Results indicate that a 30% spatial compression of vertical circulation elements—reconfiguring a 4.3-m staircase into a combined stair-escalator system—yields an approximately 5.6-fold improvement in transfer capacity under simulation-based evaluation conditions at approximately one-fifth of reconstruction cost. Four generalizable threshold conditions are identified under which micro-intervention constitutes the optimal upgrading strategy. These findings challenge the assumption that significant hub performance improvements require major reconfiguration, and provide a transferable methodological foundation for incremental hub upgrading in dense urban contexts.

Transit-Oriented Development urban rail hub micro-scale optimization spatial compression transfer efficiency station-city integration

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Supporting Agencies

  1. Funding: This research received no external funding.