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

14 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
Pages2405-2410
Number of pages6
StatePublished - Sep 29 2011
Event2011 American Control Conference, ACC 2011 - San Francisco, CA, United States
Duration: Jun 29 2011Jul 1 2011

Publication series

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

Other

Other2011 American Control Conference, ACC 2011
CountryUnited States
CitySan Francisco, CA
Period6/29/117/1/11

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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    Vemulapalli, P. K., Dean, A. J., & Brennan, S. N. (2011). Pitch based vehicle localization using time series subsequence matching with multi-scale extrema features. In Proceedings of the 2011 American Control Conference, ACC 2011 (pp. 2405-2410). [5990976] (Proceedings of the American Control Conference).