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Item type:Publication, Accessibility and the ‘everyday mobility–work–household’ triad: An exploration during the COVID-19 crisis in low-income peripheries of Lima and Bogotá(Taylor & Francis, 2024-03-22)How do people make decisions on where, when, and how to commute? And how did the pandemic crisis affect their commuting patterns? Based on exploratory interviews in Lima and family chronicles collected in Bogotá during 2020; and a second round of interviews in six low-income areas in the peripheries of these two cities during 2021, this article offers a panoramic view of the changes experienced in low-income neighbourhoods and their families during these recent years of pandemic. These changes bring to light the role of intra-household arrangements regarding mobility and accessibility. We suggest that mobility and accessibility can better be understood on a more systemic level (influenced by intra-household arrangements), as a collective phenomenon (based on the household’s resources and the household’s needs), and even as a collective decision-making process. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An to urban mobility: Data, visualization, artificial intelligent approaches, and its foundations(Universidad Simon Bolivar, 2024-01-01)In the last years, the scientific community has increasingly studied urban mobility since around 55% of the world population live in urban areas. Thus, individuals living in urban areas have to deal with phenomena like traffic jams, commute time, pollution, among others, which are difficult to understand and solve. Therefore, new innovative approaches such as mobility models, artificial intelligence, or visualization applied to urban mobility analysis problems shed new light on understanding cities’ behavior. In this work, we survey the current state of the mathematical and computational tools we have at our disposal to better understand the current situation of urban areas. Our work presents datasets, discusses relevant artificial intelligence and visualization techniques, and reviews mathematical tools to analyze urban data. We hope our work offers a valuable summary of these ideas and provides the base for future investigations.