Detection of Braking Intention during Simulated Driving Based on EEG Analysis: Online Study

Jeong Woo Kim, Il Hwa Kim, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Diversified approaches for development of braking assistant system have been employed to assure the safety of driver and pedestrian. Recently, neurophysiological studies related to driver's mental state during driving under specific conditions have been a growing interest for development of driving assistant system based on brain-computer interface (BCI). In this article, the feasibility of online braking assistant system which could detect driver's braking intention based on BCI is investigated. The results of the online experiment verified that driver's braking intention could be robustly detected based on neurophysiological characteristics proposed by previous study. The performance of the online experiment was evaluated based on reaction times for emergency situations and detection accuracy.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages887-891
Number of pages5
ISBN (Print)9781479986965
DOIs
Publication statusPublished - 2016 Jan 12
EventIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong
Duration: 2015 Oct 92015 Oct 12

Other

OtherIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
Country/TerritoryHong Kong
CityKowloon Tong
Period15/10/915/10/12

Keywords

  • Brain-Computer Interface (BCI)
  • Braking Assistant
  • Electroencephalography (EEG)
  • Online Experiment
  • Predicting Upcoming Behavior

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Information Systems and Management
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Detection of Braking Intention during Simulated Driving Based on EEG Analysis: Online Study'. Together they form a unique fingerprint.

Cite this