Advancing Shared Micromobility in Smart Cities Through Spatial Analysis and Optimization

Abstract

The rapid growth of urban populations and private vehicle ownership has exacerbated many cities' traffic congestion and environmental degradation. Shared micromobility services, including bike-sharing (BSS) and electric moped-sharing systems (EMSS), have emerged as viable solutions to these issues by providing sustainable and flexible transportation options. However, these systems face significant operational challenges, including spatial and temporal imbalances in supply and demand, as well as suboptimal infrastructure placement. While existing research has explored the influence of built environment factors on shared micromobility usage, most studies rely on global models that assume spatially uniform relationships, often overlooking the impact of spatial heterogeneity. In addition, existing spatial optimization models for locating shared micromobility stations typically evaluate demand coverage based on individual stations, without considering the dual-node nature of user trips. This simplification may result in substantial overestimation of system performance. Moreover, for EMSS, existing research has primarily focused on placing battery swapping stations, with limited attention given to the integration of parking and battery-swapping functions. Such integration is crucial for enhancing both user experience and operational efficiency, yet it remains underexplored in existing research. This dissertation addresses these gaps through three empirical studies on BSS and EMSS in Taipei. The first study examines the impact of built environments on shared micromobility usage using the Multiscale Geographically Weighted Regression model to capture spatial heterogeneity. The second study develops the Flow Termini Coverage Model (FTCM), incorporating origin-destination flow dynamics to improve the siting of bike-sharing stations. By accounting for both trip ends, the FTCM offers a more accurate representation of travel behavior than conventional single-node coverage models. The third study introduces the concept of EMSS hubs, multifunctional facilities that integrate moped rental, return, and battery-swapping, and proposes the EMSS Hub Location Problem (EHLP) model to support strategic hub placement. The EHLP provides a comprehensive framework for EMSS infrastructure planning by incorporating three types of demands. Collectively, these studies advance the shared micromobility field by developing novel spatial analytical methods and optimization models. The findings offer important implications for policy and practice, demonstrating how advanced spatial methods can support more effective and sustainable shared micromobility planning.電子版US