• DocumentCode
    3150850
  • Title

    Assessing the impact of driving behavior on instantaneous fuel consumption

  • Author

    Meseguer, Javier E. ; Calafate, Carlos T. ; Cano, Juan Carlos ; Manzoni, Pietro

  • Author_Institution
    Dept. of Comput. Eng., Univ. Politec. de Valencia, València, Spain
  • fYear
    2015
  • fDate
    9-12 Jan. 2015
  • Firstpage
    443
  • Lastpage
    448
  • Abstract
    Despite the recent technological improvements in vehicles and engines, and the introduction of better fuels, road transportation is still responsible for air pollution in urban areas due to the increasing number of circulating vehicles, and their relative travelled distances. We develop a methodology to calculate, in real-time, the consumption and environmental impact of spark ignition and diesel vehicles from a set of variables such as Engine Fuel Rate, Speed, Mass Air Flow, Absolute Load, and Manifold Absolute Pressure, all of them obtained from the vehicle´s Electronic Control Unit (ECU). Our platform is able to assist drivers in correcting their bad driving habits, while offering helpful recommendations to improve fuel economy. In this paper we will demonstrate through data mining, to what extent does the driving style really affect (negatively or positively) the fuel consumption, as well as the increase or reduction of greenhouse gas emissions generated by vehicles.
  • Keywords
    automobiles; behavioural sciences; energy consumption; fuel economy; pollution control; road vehicles; ECU; air pollution; circulating vehicles; consumption impact; diesel vehicles; drivers assistance; driving behavior; engines; environmental impact; fuel consumption; fuel economy; fuels; greenhouse gas emissions; instantaneous fuel consumption; road transportation; spark ignition; travelled distances; urban areas; vehicle electronic control unit; vehicles; Carbon dioxide; Combustion; Engines; Fuels; Global warming; Neural networks; Vehicles; Android smartphone; CO2; Driving styles; OBD-II; consumption; eco-driving; greenhouse gas emissions; instantaneous fuel consumption; neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Communications and Networking Conference (CCNC), 2015 12th Annual IEEE
  • Conference_Location
    Las Vegas, NV
  • ISSN
    2331-9860
  • Print_ISBN
    978-1-4799-6389-8
  • Type

    conf

  • DOI
    10.1109/CCNC.2015.7158016
  • Filename
    7158016