A real-time robust lane detection approach for autonomous vehicle environment

Bing-Fei Wu*, Chao Jung Chen, Chung Cheng Chiu, Tze Chiuan Lai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

This paper proposes a real-time lane detection algorithm which provides adaptive region of interesting to reduce computational load and is robust for real road environment, e.g., road inclination, road width calibration. Compared to previous approaches, the flat road assumption is released in our approach so that the result is more close to real road environment. This work has been successfully verified on highway and urban with different velocities 110km/h and 50km/h, respectively, in the real vehicle, TAIWAN iTS-1, which is an experimental car of Taiwan ITS project. The algorithm is also demonstrated on the lanes which are with shadows, texts, crooks, or sheltered by other vehicles for sunny and night environment.1.

Original languageAmerican English
Title of host publicationSixth IASTED International Conference on Signal and Image Processing
EditorsM.H. Hamza
Pages518-523
Number of pages6
StatePublished - 27 Dec 2004
EventSixth IASTED International Conference on Signal and Image Processing - Honolulu, HI, United States
Duration: 23 Aug 200425 Aug 2004

Publication series

NameSixth IASTED International Conference on Signal and Image Processing

Conference

ConferenceSixth IASTED International Conference on Signal and Image Processing
CountryUnited States
CityHonolulu, HI
Period23/08/0425/08/04

Keywords

  • Inclination
  • ITS
  • Lane detection
  • Night
  • TAIWAN iTS-1

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