A multimodal optimization framework for transitioning free-floating shared micromobility to station-based systems

This study presents a novel optimization framework for transitioning free-floating shared micromobility systems to station-based systems. Leveraging high-resolution real-world e-scooter trip data, the methodology integrates walking, public transit, and shared micromobility into a unified multimodal transport graph. A Hub Location Problem (HLP) formulation is used to jointly optimize station placement and user routing, minimizing generalized travel costs based on time and monetary factors. The model supports large-scale urban deployment and allows for incremental network expansion. Key findings indicate that shared micromobility primarily substitutes walking trips, with optimal station locations concentrated in central urban areas. While the shift to station-based systems reduces flexibility and may impact overall usage, strategic placement can preserve spatial order and enhance integration with existing transport infrastructure.