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Multi-agent System for the Recommendation of Electric Bicycle Routes

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 887))

Abstract

Nowadays, recommender systems are a key tool in sectors such as online sales, video playback and music on demand or book recommendation systems. This paper proposes a personalized route recommendation system for users of electric vehicles, specifically for e-bike users. Around the world e-bikes have become a real alternative to other motorized modes of transport and they are used for daily commuting. A multi-agent system is used to manage the information produced by the system, which generates route recommendations for users based on the routes they had travelled previously. Recommendations are provided to users through a smart-phone application, which is in charge of registering the data on the routes users travel.

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Acknowledgements

This work has been supported by the GatEBike project: Arquitectura basada en Computación Social para el control Inteligente e Interacción en Bicicletas Eléctricas. RTC-2015-4171-4. Project co-financed with Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER) funds (RETOS-COLABORACIÓN 2015). The research of Daniel Hernández de la Iglesia has been co-financed by the European Social Fund and Junta de Castilla y León (Operational Programme 2014–2020 for Castilla y León, EDU/529/2017 BOCYL). Álvaro Lozano is supported by the pre-doctoral fellowship from the University of Salamanca and Banco Santander. The research of Alberto López Barriuso has been co-financed by the European Social Fund and Junta de Castilla y León (Operational Programme 2014–2020 for Castilla y León, EDU/128/2015 BOCYL).

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Correspondence to Daniel H. de la Iglesia .

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de la Iglesia, D.H., Murciego, Á.L., Barriuso, A.L., Villarrubia, G., de Paz, J.F. (2018). Multi-agent System for the Recommendation of Electric Bicycle Routes. In: Bajo, J., et al. Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection. PAAMS 2018. Communications in Computer and Information Science, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-319-94779-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-94779-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94778-5

  • Online ISBN: 978-3-319-94779-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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