Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/40196
Título: Methodology for analyzing the travel time variability in public road transport
Autores/as: Cristóbal Betancor, Teresa
Padrón, Gabino 
Quesada-Arencibia, Alexis 
Alayón, Francisco 
García Rodríguez, Carmelo Rubén 
Clasificación UNESCO: 3327 Tecnología de los sistemas de transporte
120304 Inteligencia artificial
Palabras clave: Automatic vehicle location
Automatic. public transport planning
GPS data
Intelligent transport systems
Fecha de publicación: 2017
Editor/a: Springer 
Publicación seriada: Lecture Notes in Computer Science 
Conferencia: 11th International Conference on Ubiquitous Computing and Ambient Intelligence, (UCAmI 2017) 
Resumen: The quality of the time travel prediction is a key factor in the transport of people and goods. This prediction is used in different facets related to management and planning of the transport activity, having special influence in the service quality in public transport. In this paper a methodology to analyse the factors which affect to travel time prediction in routes of road public transport is presented. This methodology uses vehicles GPS data to identify the causes of the travel time variability, georeferencing these causes. The infrastructure elements required, data used and the processing techniques are explained. The methodology was applied to analyse the travel time of a line of a public transport company, presenting the results of this test.
URI: http://hdl.handle.net/10553/40196
ISBN: 978-3-319-67584-8
ISSN: 0302-9743
DOI: 10.1007/978-3-319-67585-5_5
Fuente: Ubiquitous Computing and Ambient Intelligence. UCAmI 2017. Lecture Notes in Computer Science, v. 10586 LNCS, p. 44-49
Colección:Capítulo de libro
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