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FI 2016

0,500
© Thomson Reuters, Journal Citation Reports, 2016

Indexada en:

SCIE /JCR, Scopus, ScienceDirect

Métricas

  • Factor de Impacto: 0,500(2016)
  • 5-años Factor de Impacto: 0,344
  • SCImago Journal Rank (SJR):0,212
  • Source Normalized Impact per Paper (SNIP):0,308

© Thomson Reuters, Journal Citation Reports, 2016

Revista Iberoamericana de Automática e Informática industrial 2014;11:435-43 - DOI: 10.1016/j.riai.2014.08.004
Algoritmo para el cálculo de la velocidad media óptima en una ruta (ASGA)
ASGA: Algorithm to obtain the optimal average speed on a route
V. Corcoba Magañaa,, , M. Muñoz Organeroa
a Departamento de Ingenier??a Telem??tica, Universidad Carlos III de Madrid, C/ Avenida de la Universidad, 30, 28911 Legan??s, Espa??a
Resumen

This paper proposes an algorithm for obtaining the optimal average speed to save fuel and improve safety. The proposed algorithm is based on genetic algorithms. The algorithm uses information about the environment, the road and the vehicle for obtaining the optimal average speed which it minimizes fuel consumption without dramatically increasing the travel time. Moreover, the proposed algorithm improves safety adapting vehicle speed to road conditions. The environment information is obtained from web services and vehicle information is obtained through the OBD2 port. The algorithm is validated in situations with and without incidents. In addition, we analyze the impact of the average speed and acceleration incidents and their impact on fuel consumption.

Resumen

En este trabajo se propone un algoritmo para obtener la velocidad media óptima para ahorrar combustible y mejorar la seguridad. El algoritmo propuesto se basa en los algoritmos genéticos. El algoritmo emplea información sobre el entorno, la carretera y el vehículo para obtener la velocidad media que minimice el consumo de combustible sin incrementar drásticamente la duración del trayecto. Además, el algoritmo propuesto mejora la seguridad ya que adecua la velocidad a las condiciones de la vía. La información sobre el entorno se obtiene de servicios web y la información sobre el vehículo se obtiene a través del puerto OBD2. El algoritmo es validado en situaciones reales con incidentes de tráfico y sin ellos. Por otra parte, se analiza el impacto de la velocidad media y los incidentes de tráfico en las aceleraciones y su influencia en el consumo de combustible.

Palabras clave
Conducción eficiente, Sistemas de ayuda a la conducción, Algoritmos Genéticos, Android, Sistemas Inteligentes de Transporte
Keywords
Eco-driving, Advanced Driver Assistance Systems, Genetic Algorithms, Android, Intelligent Transport System
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Autor para correspondencia. vcorcoba@it.uc3m.es (V. Corcoba Magaña vcorcoba@it.uc3m.es)