Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43560
Title: Arrival time estimation system based on massive positioning data of public transport vehicles
Authors: Padrón, Gabino 
Alayón, Francisco 
Cristóbal, Teresa
Quesada-Arencibia, Alexis 
García, Carmelo R. 
UNESCO Clasification: 120304 Inteligencia artificial
3327 Tecnología de los sistemas de transporte
Keywords: Intelligent transport systems
Float car data
Pattern recognition
Artificial intelligence
Bus transportation
Traffic control
Issue Date: 2016
Journal: Lecture Notes in Computer Science 
Conference: 10th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI) 
Abstract: 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
Source: García C., Caballero-Gil P., Burmester M., Quesada-Arencibia A. (eds) Ubiquitous Computing and Ambient Intelligence. IWAAL 2016, AmIHEALTH 2016, UCAmI 2016. Lecture Notes in Computer Science, vol 10070. Springer, Cham
Appears in Collections:Actas de congresos
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