Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/43560
Título: | Arrival time estimation system based on massive positioning data of public transport vehicles | Autores/as: | Padrón, Gabino Alayón, Francisco Cristóbal, Teresa Quesada-Arencibia, Alexis García, Carmelo R. |
Clasificación UNESCO: | 120304 Inteligencia artificial 3327 Tecnología de los sistemas de transporte |
Palabras clave: | Intelligent transport systems Float car data Pattern recognition Artificial intelligence Bus transportation, et al. |
Fecha de publicación: | 2016 | Editor/a: | Springer | Publicación seriada: | Lecture Notes in Computer Science | Conferencia: | 10th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2016) | Resumen: | Nowadays the public transport systems play a main role in the advanced societies. How to evaluate the quality of the public transport is a critic task of the transport regulatory agencies. One indicator used to measure this quality is the fulfilment of the scheduled operation by the transport operators, specially scheduled arrival times and frequencies at stops. In this paper, an automatic system to estimate arrival times in the context of road public transport is proposed. The system works autonomously, acquiring massive vehicle position readings, registering and processing them automatically in order to estimate arrival times. This autonomous behaviour is achieved using pattern recognition and statistical techniques. To illustrate the application of the system, the estimation of arrival times at a bus stop is presented. | URI: | http://hdl.handle.net/10553/43560 | ISBN: | 978-3-319-48798-4 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-319-48799-1_44 | Fuente: | Ubiquitous Computing and Ambient Intelligence. IWAAL 2016, AmIHEALTH 2016, UCAmI 2016. Lecture Notes in Computer Science, v. 10070, p. 395-406 |
Colección: | Capítulo de libro |
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