Résumé
The growth of urban population and, consequently, the number ofvehicles causes the increase of traffic jams and emission of polluting gases. Inthis context, we observe the intensification of papers that aim to identify bottle-necks and their causes. These papers propose methodologies that use trajectorydata model and aim to explain systemic behaviors. This article proposes theidentification and classification of anomalies in the urban road transport systemfrom space-time aggregations to permanent objects. The methodology consistsof pre-processing of data, identification of anomalies, identification, and clas-sification of frequent patterns. Through it, we can identify the systemic andspecific behaviors on the urban transit of Rio de Janeiro.