Development of driving support system for electric vehicle by using image processing technology

Yuxiang Sun*, Nan Wu, Shigeyuki Tateno, Harutoshi Ogai

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Aiming to realize the safe driving for the elderly people and novice drivers, intelligent vehicle technologies are becoming an important research topic in recent years. While driving, sometimes they cannot handle the car in an emergency due to the poor concentration and reaction. In fact, there are a lot of car accidents caused by such people who occasionally step on the accelerator instead of the brake unexpectedly when intending to have an emergency stopping. This paper describes a recognition method for recognizing driving situation. For supporting driving by traffic situation recognition, real-time detection and robustness are increasingly required. In indoor experiments, the RoboCar was used to verify the recognition methods. The algorithm which determines the routes are able to run safety by the CCD camera was used to recognize the white line on both sides of the road. And the image matching algorithm was used to recognize the traffic signs on the routes. The experimental result with high accuracy was successfully obtained.

Original languageEnglish
Title of host publicationICCAS 2012 - 2012 12th International Conference on Control, Automation and Systems
Pages1965-1968
Number of pages4
Publication statusPublished - 2012 Dec 1
Event2012 12th International Conference on Control, Automation and Systems, ICCAS 2012 - Jeju, Korea, Republic of
Duration: 2012 Oct 172012 Oct 21

Publication series

NameInternational Conference on Control, Automation and Systems
ISSN (Print)1598-7833

Conference

Conference2012 12th International Conference on Control, Automation and Systems, ICCAS 2012
Country/TerritoryKorea, Republic of
CityJeju
Period12/10/1712/10/21

Keywords

  • Electric Vehicle
  • Image Matching
  • Image Processing
  • Sign Recognition
  • White Line Recognition

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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