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Reducing Stress and Fuel Consumption Providing Road Information

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Ambient Intelligence - Software and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 376))

Abstract

In this paper, we propose a solution to reduce the stress level of the driver, minimize fuel consumption and improve safety. The system analyzes the driving and driver workload during the trip. If it discovers an area where the stress increases and the driving style is worse from the point of view of energy efficiency, a photo is taken and is saved along with its location in a shared database. On the other hand, the solution warns the user when is approaching a region where the driving is difficult (high fuel consumption and stress) using the shared database. In this case, the proposal shows on the screen of the mobile device the image captured previously of the area. The aim is that driver knows in advance the driving environment. Therefore, he or she may adjust the vehicle speed and the driver workload decreases. Data Envelopment Analysis is used to estimate the efficiency of driving and driver workload in each area. We employ this method because there is no preconceived form on the data in order to calculate the efficiency and stress level. A validation experiment has been conducted with 6 participants who made 96 driving tests in Spain. The system reduces the slowdowns (38 %), heart rate (4.70 %), and fuel consumption (12.41 %). The proposed solution is implemented on Android mobile devices and does not require the installation of infrastructure on the road. It can be installed on any model of vehicle.

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Acknowledgments

The research leading to these results has received funding from the “HERMES-SMART DRIVER” project TIN2013-46801-C4-2-R within the Spanish “Plan Nacional de I + D+I” under the Spanish Ministerio de Economía y Competitividad and from the Spanish Ministerio de Economía y Competitividad funded projects (co-financed by the Fondo Europeo de Desarrollo Regional (FEDER)) IRENE (PT-2012-1036-370000), COMINN (IPT-2012-0883-430000) and REMEDISS (IPT-2012-0882-430000) within the INNPACTO program.

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Authors and Affiliations

  1. Dpto. de Ingeniería Telemática, Universidad Carlos III de Madrid Leganés, Madrid, Spain

    Víctor Corcoba Magaña & Mario Muñoz Organero

Authors
  1. Víctor Corcoba Magaña
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  2. Mario Muñoz Organero
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Corresponding author

Correspondence to Víctor Corcoba Magaña .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering Department, Qatar University, College of Engineering, Doha, Qatar

    Amr Mohamed

  2. Departamento de Informatica, ALGORITMI Centre, University of Minho, Braga, Portugal

    Paulo Novais

  3. Escola Superior de Tecnologia e Gestäo de Leiria, Instituto Politécnico de Leiria, Leiria, Portugal

    António Pereira

  4. Departamento de Informática y Automática, University of Salamanca, Salamanca, Spain

    Gabriel Villarrubia González

  5. Departamento de Sistemas Informáticos, University of Castilla-La Mancha, Albacete, Spain

    Antonio Fernández-Caballero

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Magaña, V.C., Organero, M.M. (2015). Reducing Stress and Fuel Consumption Providing Road Information. In: Mohamed, A., Novais, P., Pereira, A., Villarrubia González, G., Fernández-Caballero, A. (eds) Ambient Intelligence - Software and Applications. Advances in Intelligent Systems and Computing, vol 376. Springer, Cham. https://doi.org/10.1007/978-3-319-19695-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-19695-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19694-7

  • Online ISBN: 978-3-319-19695-4

  • eBook Packages: EngineeringEngineering (R0)

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