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Road grade estimation results using sensor and data fusion
Scania CV AB, Södertälje.
Scania CV AB, Södertälje.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2007 (English)In: 14th World Congress on Intelligent Transport Systems, ITS 2007, 2007, 5206-5217 p.Conference paper, Published paper (Refereed)
Abstract [en]

Advanced driver assistance systems for heavy duty vehicles, such as lookahead cruise and gearshift controllers, rely on high quality map data. Current digital maps do not offer the required level of road grade information. This contribution presents an algorithm for on-board road grade estimation based on fusion of GPS and vehicle sensor data with measurements from previous runs over the same road segment. An incremental update scheme is utilized to ensure that data storage requirements are independent of the number of measurement runs. Results of the implemented system based on six traversals of a known road with three different vehicles are presented.

Place, publisher, year, edition, pages
2007. 5206-5217 p.
Keyword [en]
Roads and streets, Sensor data fusion, Sensors, Traffic control
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-81163Scopus ID: 2-s2.0-84893529011ISBN: 978-161738777-7 (print)OAI: oai:DiVA.org:kth-81163DiVA: diva2:497197
Conference
14th World Congress on Intelligent Transport Systems, ITS 2007; Beijing; China; 9 October 2007 through 13 October 2007
Note

QC 20120216

Available from: 2012-02-16 Created: 2012-02-10 Last updated: 2014-10-27Bibliographically approved

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Type fulltextMimetype application/pdf

Scopus

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Johansson, Karl Henrik

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf