Robust vision based lane tracking using multiple cues and particle filtering

Nicholas Apostoloff*, Alexander Zelinsky

*Corresponding author for this work

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

    145 Citations (Scopus)

    Abstract

    One of the more startling effects of road related accidents is the economic and social burden they cause. Between 750,000 and 880,000 people died globally in road related accidents in 1999 alone, with an estimated cost of US$518 billion. One way of combating this problem is to develop Intelligent Vehicles that are self-aware and act to increase the safety of the transportation system. This paper presents the development and application of a novel multiple-cue visual lane tracking system for research into Intelligent Vehicles (IV). Particle filtering and cue fusion technologies form the basis of the lane tracking system which robustly handles several of the problems faced by previous lane tracking systems such as shadows on the road, unreliable lane markings, dramatic lighting changes and discontinuous changes in road characteristics and types. Experimental results of the lane tracking system running at 15 Hz will be discussed, focusing on the particle filter and cue fusion technology used.

    Original languageEnglish
    Title of host publicationIEEE Intelligent Vehicles Symposium, Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages558-563
    Number of pages6
    ISBN (Electronic)0780378482
    DOIs
    Publication statusPublished - 2003
    Event2003 IEEE Intelligent Vehicles Symposium, IV 2003 - Columbus, United States
    Duration: 9 Jun 200311 Jun 2003

    Publication series

    NameIEEE Intelligent Vehicles Symposium, Proceedings

    Conference

    Conference2003 IEEE Intelligent Vehicles Symposium, IV 2003
    Country/TerritoryUnited States
    CityColumbus
    Period9/06/0311/06/03

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