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Pitch based vehicle localization using time series subsequence matching with Multi-scale Extrema Features

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3 Author(s)
Pramod K. Vemulapalli ; Department of Mechanical Engineering, The Pennsylvania State University, State College, 16803, USA ; Adam J. Dean ; Sean N. Brennan

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.

Published in:

Proceedings of the 2011 American Control Conference

Date of Conference:

June 29 2011-July 1 2011