• DocumentCode
    678068
  • Title

    Experiment Design for Measuring Driver Reaction Time in Driving Situation

  • Author

    Zhong Zhang ; Asakawa, Yuki ; Imamura, Takashi ; Miyake, Tetsuo

  • Author_Institution
    Dept. of Mech. Eng., Toyohashi Univ. of Technol., Toyohashi, Japan
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    3699
  • Lastpage
    3703
  • Abstract
    Generally, inattentive driving is driving while in a state where attention has been weakened by a psychological factor. As a result, either the driver does not realize this condition or realization is delayed. In order to evaluate inattentive driving, the authors constructed a neural network-based NARX model for each driver using operation signals of neutral driving without secondary tasks and inattentive driving without secondary tasks and made the difference between the neutral driving and inattentive driving clear. However, the influence of the secondary task for inattentive driving is different for different drivers. Therefore, the problem is how to examine drivers´ characteristics. In this study, in order to examine drivers´ characteristics, we designed an experiment to measure a driver´s reaction time, which is an important driver characteristic, by using a driving simulator, and obtained encouraging results.
  • Keywords
    design of experiments; digital simulation; driver information systems; neural nets; driver characteristic; driver reaction time measurement; driving simulator; driving situation; experiment design; inattentive driving; neural network-based NARX model; neutral driving; operation signals; psychological factor; Conferences; Cybernetics; Driving simulator; driver carelessness states; driver reaction time; inattentive driving; second task;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.630
  • Filename
    6722383