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EEG Signals-Based Longitudinal Control System for a Brain-Controlled Vehicle

  • Yun Lu
  • , Luzheng Bi*
  • *Corresponding author for this work
  • Beijing Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Directly using brain signals to drive a vehicle may not only help persons with disabilities to regain driving ability but also provide a new alternative way for healthy people to control a vehicle. In this paper, we propose a new longitudinal control system based on electroencephalogram signals for brain-controlled vehicles (BCVs) by combining a user interface, a brain-computer interface (BCI) system, and a longitudinal control module. Driver-in-the-loop experiments were conducted by using two driving tests (i.e., the destination-approaching and car-following tests) with different subjects under two control conditions, i.e., the brain and manual control conditions. Experimental results show the feasibility of alone using brain signals to continuously perform the longitudinal control of a vehicle at a relatively high speed, at least for some users. This paper not only promotes the development of BCVs but also provides some insights into the research on how to apply BCIs to control other high-speed dynamic systems.

Original languageEnglish
Pages (from-to)323-332
Number of pages10
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume27
Issue number2
DOIs
Publication statusPublished - 1 Feb 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Brain-controlled vehicles (BCVs)
  • EEG
  • human-vehicle interaction
  • longitudinal control

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