Estimation of Longitudinal Driving Intention Based on Statistical Method Using Electroencephalogram

For a functional driver assistance system to work property and provide cooperation between the driver and the vehicle, it must be configured to fit the preference of the driver. A brain–computer interface (BCI) provides communication between the driver and vehicle by translating human intentions, as reflected by brain signals represented in an electroencephalogram (EEG). This paper presents an algorithm for classifying a driver’s operational intentions, based on a BCI that uses data from an EEG. Experiments were conducted with six able-bodied subjects, with varying driving experience, using a driving simulator (DS). The drivers were instructed to operate the vehicle according to the series of three kinds of instructions (gas pedal, brake pedal, and keep). Those instructions were given to the subject with random order, after the operation trigger had been signaled. The off-line estimation results show that the driver's longitudinal intentions can be classified with accuracy for about 70% for all subjects.

Language

  • English

Media Info

  • Media Type: CD-ROM
  • Features: Figures; Photos; References; Tables;
  • Pagination: 11p
  • Monograph Title: ITS in Daily Life

Subject/Index Terms

Filing Info

  • Accession Number: 01148291
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jan 5 2010 12:54PM