Analyzing intrapersonal variability in mobility patterns (i.e., how individuals’ daily travel behaviors, such as destination and route choice, change over time) requires multi-day datasets, which are not commonly available for transportation research. This paper presents a method for deriving mobility patterns from mobile phone data and examines their relationship with multiple socioeconomic indicators. Specifically, we used Call Detail Records (CDR) from 77 days in selected areas, representing individuals living in or near low-income areas (favelas). This allows us to compare the intrapersonal variability of different social groups. While CDR has been used in mobility inequality studies, this paper is the first to examine intrapersonal variability inequalities among favela dwellers using this data source, addressing gaps in multi-day studies in unequal contexts of the Global South. We developed a Poisson model with interaction variables to assess the influence of socioeconomic and land-use variables on mobility variability during weekdays. By controlling for these variables, we demonstrate that a lower income is associated with higher variability, which may be attributed to job informality, while higher-income groups exhibit more stable routines. Furthermore, favela dwellers exhibit lower variability between the weekdays despite economic precarity, suggesting that spatial constraints (e.g., limited transportation options or localized informal economies) override income effects. Our research shows that CDR can be a valuable source for multi-day analyses to examine mobility patterns to address urban inequalities, providing insights for improving urban transportation policies, such as including targeted interventions for informal workers and favela-specific mobility solutions.
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