Pitch based vehicle localization using time series subsequence matching with multi-scale extrema features

Pramod K. Vemulapalli, Adam J. Dean, Sean N. Brennan

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

17 Scopus citations

Abstract

Non-GPS localization of vehicles on roadways has received considerable attention in recent years and a number of solutions have been proposed, with most solutions addressing local tracking. This paper presents an algorithm that achieves global localization within very large road networks using pitch information. A key contribution is the development of the Multi-scale Extrema Feature that provides a number of advantages over traditional time-series subsequence matching methods in order to implement the above scheme. The algorithm's results in localizing a vehicle's position without initialization within a road network spanning 6000 Km are also presented.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 American Control Conference, ACC 2011
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2405-2410
Number of pages6
ISBN (Print)9781457700804
DOIs
StatePublished - 2011

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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