• DocumentCode
    2515069
  • Title

    Modular approach to energy efficient driver assistance incorporating driver acceptance

  • Author

    Themann, Philipp ; Eckstein, Lutz

  • Author_Institution
    Inst. fur Kraftfahrzeuge Aachen (ika), RWTH Aachen Univ., Aachen, Germany
  • fYear
    2012
  • fDate
    3-7 June 2012
  • Firstpage
    1023
  • Lastpage
    1028
  • Abstract
    The deployment of predictive driving styles reduces fuel consumption of vehicles significantly, while assistance systems can support drivers in this task. This paper describes a modular approach to consider various sources of information as well as different driver and vehicle types in the prediction and the optimization of the vehicle´s longitudinal dynamics to reduce fuel consumption. Energy efficient driving strategies such as roll out or fuel cut-off are compared to the average driving behavior of the driver. The utility of the efficient strategies is assessed relative to the average driver behavior, which is similar to human information processing. Resulting optimal driving strategies are provided to the driver as recommendations or applied to vehicles by intervening assistance systems such as adaptive cruise control. This paper aims to summarize the basic methodology of the approach.
  • Keywords
    adaptive control; control engineering computing; driver information systems; energy conservation; road traffic; adaptive cruise control; driver acceptance; energy efficient driver assistance; fuel consumption reduction; predictive driving; Adaptation models; Energy efficiency; Fuels; Humans; Mathematical model; Predictive models; Vehicles; C2I; C2X; cooperative technologies; driver acceptance; energy efficiency; green driving; predictive driving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium (IV), 2012 IEEE
  • Conference_Location
    Alcala de Henares
  • ISSN
    1931-0587
  • Print_ISBN
    978-1-4673-2119-8
  • Type

    conf

  • DOI
    10.1109/IVS.2012.6232116
  • Filename
    6232116