Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/40196
Title: Methodology for analyzing the travel time variability in public road transport
Authors: Cristóbal Betancor, Teresa
Padrón, Gabino 
Quesada-Arencibia, Alexis 
Alayón, Francisco 
García Rodríguez, Carmelo Rubén 
UNESCO Clasification: 3327 Tecnología de los sistemas de transporte
120304 Inteligencia artificial
Keywords: Automatic vehicle location
Automatic. public transport planning
GPS data
Intelligent transport systems
Issue Date: 2017
Journal: Lecture Notes in Computer Science 
Conference: 11th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2017 
Abstract: 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: 9783319675848
ISSN: 0302-9743
DOI: 10.1007/978-3-319-67585-5_5
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 10586 LNCS, p. 44-49
Appears in Collections:Actas de congresos
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