Model Structure, Realization and Learning Process For a Driver Model Being Capable to Improve Performance with Learning by Itself

  • Kazuhide Togai
  • Hisashi Tamaki
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 196)


Vehicle electrification has been extended rapidly in a recent few years and development work for those has been added to conventional vehicles. Model based development (MBD) methodologies have been adopted widely. A dynamic driver model is required for controller design considering driver’s behaviour and for verification with SiLS and HiLs in the MBD process. Some higher response and multi-variable control systems can be constructed with electronic devices. However, human control is not so quicker and not capable to handle multi states. There have been a lot of published papers regarding to driver models. Structure of the driver model with constrains of human property and learning process seems to be under study. Authors have investigated driver models for target speed tracking driving in emission test cycles in which the target is clearly defined. Taking account of constrains with driver’s response and information processing capability, a driver model structure, feed forward operation based on prediction and additional error feedback correction, is introduced. A learning algorithm to obtain inverse vehicle property for the feed forward control is proposed. Knowledge which enables to select features to be learned and condition for stable learning process are discussed. Numerical simulation illustrates driving behaviour from a beginner to an expert with the driver model. Further, it is shown that speed tracing driving performance with a novice driver model could be improved when vehicle property is changed, e.g. an IC engine is replaced by an electric motor. It is supposed that the proposed method is also applicable to development process for a lower order and rower sample rate controller with adaptation functionality.


Driver model Learning control Software in the loop simulation Rapid prototyping Emission test cycle 


  1. 1.
    Macadam CC (2003) Understanding and modeling the human driver, vehicle system dynamics. Taylor & Francis, UKGoogle Scholar
  2. 2.
    Kageyama I (2007) Construction of driver model for analyzing driver behavior, JSAE20075284, JSAE annual congress 2007 SpringGoogle Scholar
  3. 3.
    Togai K (2010) Powertrain model selection and reduction for real time control algorithm design and verification in rapid controller prototyping environment SAE2010-01-0236Google Scholar
  4. 4.
    Hendrics E (1991) SI engine controls and mean value engine modeling. SAE910258Google Scholar
  5. 5.
    Kotwicki AJ (1982) Dynamic models for torque converter equipped vehicles. SAE820393Google Scholar
  6. 6.
    Danno Y, Togai K (1989) Powertrain control by DBW system: strategy and modeling. SAE 890760, pp 85–98, SP788Google Scholar
  7. 7.
    Togai K, Tamaki H (2010) Human driving behaviour analysis and model representation acquisition of meta-knowledge and expertise acquiring process. AVEC’10Google Scholar
  8. 8.
    Togai K, Tamaki H (2008) Emission test cycle driving agent and expertise in driving behavior. Rev Automot Eng JSAE 29(3):93–97Google Scholar
  9. 9.
    Kageyama I (2005) Study on evaluation of driver’s behavior at running on narrow road. Proc JSAE Annu Congr Autumn 2005Google Scholar
  10. 10.
    Lio F, Egami T, Tsuchiya T, Yu X (1996) On general type of digital optimal preview servo system. Appl Math Mech 17(5):423–436Google Scholar
  11. 11.
    Arimoto S, Kawamura S (1984) Bettering operation of robotics. J Rob Syst 1–2:123–140CrossRefGoogle Scholar
  12. 12.
    Ito M (2009) Control mechanisms that we learn from the brain. J Soc Automot Eng Jpn 63(5)Google Scholar
  13. 13.
    Carlo Cacciabue P (eds) (2007) Modelling driver behaviour in automotive environments: critical issues in driver interactions with intelligent transport systems. Springer, New YorkGoogle Scholar
  14. 14.
    Togak K, Tamaki H (2011) Human driving behavior analysis and model representation with expertise acquiring process for controller rapid prototyping. SAE2011-01-0051Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Kobe UniversityHyōgoJapan

Personalised recommendations