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dc.date.accessioned 2015-12-11T12:57:57Z
dc.date.available 2015-12-11T12:57:57Z
dc.date.issued 2015-11
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/50136
dc.description.abstract The discovery of moving objects trajectory patterns representing a high traffic density have been covered on different works using diverse approaches. These models are useful for the areas of transportation planning, traffic monitoring and advertising on public roads. Besides of the important utility, these type of patterns usually do not specify a difference between a high traffic and a traffic congestion. In this work, we propose a model for the discovery of high traffic flow patterns and traffic congestions, represented in the same pattern. Also, as a complement, we present a model that discovers alternative paths to the severe traffic on these patterns. These proposed patterns could help to improve traffic allowing the identification of problems and possible alternatives. en
dc.format.extent 81-86 es
dc.language en es
dc.subject Patterns (e.g., client/server, pipeline, blackboard) es
dc.subject road network en
dc.subject traffic flow en
dc.title Representing traffic congestions on moving objects trajectories en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST41-Paper-6.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Kohan, Mariano es
sedici.creator.person Ale, Juan María es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution 3.0 Unported (CC BY 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by/3.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 15, no. 2 es


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Creative Commons Attribution 3.0 Unported (CC BY 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution 3.0 Unported (CC BY 3.0)