Quintieri, Carlos Eduardo Saraiva; Amaral, Victor Figueiredo; Kechichian, Vitor de Sá (2024-06-07)
Faculdade de Computação e Informática (FCI)
In the context of smart cities, the application of Artificial Intelligence techniques in urban traffic presents significant potential for improving various economic and social aspects, as well as the quality of life for citizens. This work focused on exploring the use of the Ant Colony Optimization (ACO) algorithm to analyze urban traffic data from the city of São Paulo. The aim is to provide a form of analysis that supports urban managers in identifying routes with a higher flow of people. The experimental results identified critical paths, highlighting sensitive areas along urban routes and providing useful information to managers. The analysis of real public data on people traffic demonstrates that it is possible to offer insights for the enhancement of urban mobility and the promotion of improved quality of life for the population of this large metropolis.
