Abstract
Integrating micro-mobility services with high-capacity public transit networks is a crucial pathway toward reducing private vehicle reliance and fostering sustainable urban mobility. This study presents a hybrid methodology combining Spatial Network Analysis (SNA) and Agent-Based Modeling (ABM) to evaluate and optimize first/last-mile (FLM) connectivity around Utrecht Centraal, the busiest railway hub in the Netherlands. By mapping the local pedestrian and cycling infrastructure using space syntax metrics (integration and choice), we identified structural bottlenecks in the urban fabric. These spatial parameters were integrated into an ABM environment to simulate the daily commuting behaviors of 10,000 heterogeneous agents, testing three planning scenarios: a baseline, a decentralized micro-mobility docking strategy, and an integrated infrastructure scenario featuring dedicated micro-mobility lanes. The simulation results indicate that decentralized docking stations coupled with targeted spatial interventions reduce average FLM travel times by 18.4% and increase overall public transit utility by 12.2%. Crucially, the spatial network analysis revealed that micro-mobility integration is highly sensitive to local street connectivity, showing that infrastructure investments yield the highest returns when aligned with high-choice urban corridors. These findings provide urban planners and transit authorities with a predictive, spatially explicit decision-support framework to design resilient, human-centered multi-modal transit hubs.
