Terrain-based vehicle localization from real-time data using dynamical models

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

Abstract

This paper describes a novel method for the location of road vehicles using vehicle pitch data obtained from on-board sensors. The method encodes the road map data using linear dynamical models, and then, during travel, identifies the vehicle location through continuous validation of the previously obtained linear models. The approach presented has several advantages over previous approaches in the literature, namely a smaller computational burden, a more definitive location estimate, and a simplified and more direct way of handling common types of noise. These benefits have the potential to both increase the speed of the localization and to reduce the implementation cost of terrain-based localization. The method is tested in simulation using real-world road data collected in State College PA, USA. Performance is demonstrated both in a noise-free and noisy environments, and a bound is shown on the convergence distance.

Original languageEnglish (US)
Article number6426351
Pages (from-to)3366-3371
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
StatePublished - Dec 1 2012
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: Dec 10 2012Dec 13 2012

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'Terrain-based vehicle localization from real-time data using dynamical models'. Together they form a unique fingerprint.

Cite this