Estimation of Longitudinal Driving Intention Based on Statistical Method Using Electroencephalogram Ikenishi, Toshihito ; Machida, Yutaka ; Kamada, Takayoshi ; Nagai, Masao
Publication details: Bryssel ITS in daily life: 16th world congress and exhibition on intelligent transport systems and services, Stockholm 21-25 September 2009. Paper, 2009Description: 11 sSubject(s): Bibl.nr: VTI P1835:16 [World]Location: Abstract: 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.| Current library | Status | |
|---|---|---|
| Statens väg- och transportforskningsinstitut | Available |
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.