Spatio-temporal Analysis of Micromobility Sharing in the City of Rome

This study examines the demand for shared micromobility in Rome, focusing on free-floating bike and e-scooter sharing services, using a dataset that overcomes the limitations of GBFS data. Unlike GBFS, which is typically used for station-based systems and presents challenges for free-floating services (due to frequent vehicle ID rotations and difficulties in tracking trips), this dataset is provided by Roma Mobilità and includes over 9 million trips recorded between 2022 and 2023 from seven service providers. The analysis reveals how usage patterns are influenced by seasonal variations, weather conditions, and tourist flow, with a clear preference for e-scooters in warmer months and more consistent bicycle usage in milder conditions. The highest trip volumes occur in summer, with peaks in July for e-scooters and October for bicycles. Spatially, areas with restaurants, residential buildings, and public transport connections generate the most trips. By applying a Zero-Inflated Poisson regression, the study identifies key factors influencing trip generation and attraction, providing actionable insights for urban planning. These results offer valuable guidance to optimize the deployment of shared micromobility services, enhance infrastructure, and improve user experience, ultimately making shared mobility solutions more efficient and effective for users, service providers, and the community.