Abstract

The spread of the Covid-19 virus all around the globe drastically changed our lifestyles and our habits. Among all aspects affected by the pandemic, mobility certainly underwent huge changes. Recognizing these shifts in transportation behaviors enables urban planners to tailor infrastructure and policies, ensuring effective transit in the aftermath of the pandemic. This work consists in a data-intensive study of the Padova bike sharing system in Italy, which we utilized as case study, to understand the enduring effects of the pandemic. To this end, we retrieved, pre-processed and analyzed the data relative to three periods that are representative of pre-pandemic, pandemic, and post-pandemic worlds. We combined the bike-sharing data with geographical, meteorological, and user information. We then performed both a temporal and a spatial-temporal analysis, by generating a graph from the rides network. By analysing the rides graph properties and connectivity, we observed an increase in the total amount of rides, as well as an expansion of the service toward more peripheral areas, and a greater predisposition to use the bike-sharing system.

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