Mobility is a complex phenomenon shaped by different environmental components such as people's behaviour, socio-economic factors, and the available infrastructures. People regularly travel within their surrounding environment with very different motivations. Their mobility patterns can be highly heterogeneous due to personal propensity or social segregation owing to invisible cultural, social or economic barriers. From this perspective, modelling and understanding travel allocation strategies of people are critical tasks to conceive new solutions to promote equal access to urban mobility and to minimize the carbon footprint. Here, starting from the notion of Adjacent Possible, we present a review of the most promising tools to detect and quantify mobility patterns. Based on High-Frequency Location-Based data on the metropolitan area of Rome, our analyses reveal several interesting insights. Among them, the balance between exploration and exploitation in anonymous individuals' mobility history, highly heterogeneous accessibility patterns, the clustering of users according to their mobility habits, the differences in the visited locations and the possibility to correlate them to socio-economic indicators.
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