Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/40197
Title: System model for a continuous improvement of road mass transit
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 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 service has a main relevance in mass transit systems, being the reliability a key factor for this quality. A system model for the continuous transport data acquisition and computing of these data to improve the quality of service of road mass transit systems is presented in this contribution. This proposal has been conceived to provide services adapted to the needs of the travellers by a continuous monitoring of the transport activity. The data obtained by buses on boarded systems have a special relevance in the proposed model, specially the data provided by the on boarded sensors, such as GPS positioning system. The system model has been applied to analyse the reliability of the operation scheduling of a road mass transit operator, and the results of this test are presented in this paper.
URI: http://hdl.handle.net/10553/40197
ISBN: 9783319675848
ISSN: 0302-9743
DOI: 10.1007/978-3-319-67585-5_22
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. 207-212
Appears in Collections:Actas de congresos
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