Designing green and safe micro mobility routes: An advanced geo-analytic decision system based approach to sustainable urban infrastructure

Urban mobility faces increasing challenges due to congestion, environmental concerns, and inefficiencies in transport infrastructure. Micro-mobility solutions have gained significant attention as a sustainable alternative, yet their integration into urban transport networks remains a complex task. To this end, this study introduces a geo-analytic decision-making framework for optimizing micro-mobility route planning. The methodology consists of five key steps: (i) identification and spatial analysis of 33 critical factors influencing micro-mobility adoption in a Geographic Information Systems (GIS) environment; (ii) a suitability map for the routes was generated using the state-of-the-art Fuzzy Logarithm Methodology of Additive Weights (FLMAW) and Fuzzy Simple Weight Calculation (fuzzy SIWEC) weighting methods. It was determined that criteria such as cyclist lanes, public transportation routes, terrain inclination, and recreational areas have a high impact on micro mobility use; (iii) based on this analysis, 21 optimized routes were developed, and their relationships with the main criteria were validated through Spearman’s rank correlation analysis, revealing a significant and strong positive correlation; (iv) additionally, Random Forest classification was applied to categorize routes into nine different usage classes. Route classes with different nicknames such as GreenLink and UrbanHealth Path have been created; and (v) DOmbi Bonferroni (DOBI) performance evaluation method was used to determine the preferred priority order for route construction in the study area. The results indicate that the construction priority of routes R9 and R10 is higher than that of other routes. The proposed framework offers a scalable, adaptable, data-driven, and evidence-based approach, providing valuable insights for urban planners and policymakers aiming to integrate micro-mobility into sustainable transportation strategies.