Detecçao de Anomalias Frequentes no Transporte Rodoviario Urbano - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2018

Detecçao de Anomalias Frequentes no Transporte Rodoviario Urbano

Abstract

The growth of urban population and, consequently, the number of vehicles causes the increase of traffic jams and emission of polluting gases. In this context, we observe the intensification of papers that aim to identify bottle- necks and their causes. These papers propose methodologies that use trajectory data model and aim to explain systemic behaviors. This article proposes the identification and classification of anomalies in the urban road transport system from space-time aggregations to permanent objects. The methodology consists of pre-processing of data, identification of anomalies, identification, and clas- sification of frequent patterns. Through it, we can identify the systemic and specific behaviors on the urban transit of Rio de Janeiro.
O crescimento da populac¸ ˜ao urbana e, consequentemente, do n´umero de ve´ıculos provoca o aumento de engarrafamentos e da emiss˜ao de ga- ses poluentes. Nesse contexto, observa-se a intensificac¸ ˜ao de pesquisas que buscam identificar engarrafamentos e suas causas. Estas pesquisas prop˜oem metodologias que usam modelo de dados de trajet´oria e visam ex- plicar comportamentos sistˆemicos. Este artigo prop˜oe a identificac¸ ˜ao e a classificac¸ ˜ao de anomalias no sistema de transporte rodovi´ario urbano a partir de agregac¸ ˜oes espac¸o-temporais a objetos permanentes. A metodologia con- siste do pr´e-processamento dos dados, identificac¸ ˜ao de anomalias, identificac¸ ˜ao e classificac¸ ˜ao de padr˜oes frequentes. Por meio dela, ´e poss´ıvel identificar com- portamentos sistˆemicos e pontuais do trˆansito urbano do Rio de Janeiro.
Fichier principal
Vignette du fichier
271-sbbd_2018-sp.pdf (133.02 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

lirmm-01868597 , version 1 (05-09-2018)

Identifiers

  • HAL Id : lirmm-01868597 , version 1

Cite

Ana Beatriz Cruz, João Ferreira, Diego Carvalho, Eduardo Mendes, Esther Pacitti, et al.. Detecçao de Anomalias Frequentes no Transporte Rodoviario Urbano. SBBD: Simpósio Brasileiro de Banco de Dados, SBC, Aug 2018, Rio de Janeiro, Brazil. pp.271-276. ⟨lirmm-01868597⟩
213 View
188 Download

Share

Gmail Facebook X LinkedIn More