abstract 93

Bulletin of Computational Applied Mathematics (Bull CompAMa) 

93

An Introduction to Urban Mobility: Data, Visualization, Artificial Intelligent Approaches, and Its Foundations (Research Paper)

Hugo Alatrista-Salas, Erick Cuenca, Rigoberto Fonseca-Delgado, Saba Infante, Raúl Manzanilla, Diego Morales-Navarrete, Aracelis Hernandez, Miguel Nunez-del-Prado, Israel Pineda, Pascal Poncelet, Arnaud Sallaberry.

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.

Keywords: Urban mobility; data visualization; data interpolation; data adjustment.

Cite this paper:

Alatrista-Salas H., Cuenca E., Fonseca-Delgado R., Infante S., Manzanilla R., Morales-Navarrete D., Hernandez A., Nunez-del-Prado M., Pineda I., Poncelet P., Sallaberry A.

An Introduction to Urban Mobility: Data, Visualization, Artificial Intelligent Approaches, and Its Foundations

Bull. Comput. Appl. Math. (Bull CompAMa)

Vol. 12, No.1 pp.119-143, 2024.