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A sensor and data fusion algorithm for road grade estimation
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
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)Conference paper, Published paper (Refereed)
Abstract [en]

Emerging driver assistance systems, such as look-ahead cruise controllers for heavy duty vehicles, require high precision digital maps. This contribution presents a road grade estimation algorithm for fusion of GPS and vehicle real-time sensor data, with measurements from previous runs over the same road segment. The resulting road grade estimate is thus enhanced using measurements from additional traversals of known roads. Distributed data fusion is utilized to ensure that the storage requirement of known roads does not increase when additional measurements are processed. The implemented algorithm, which is based on extended Kalman filtering and smoothing, is described in detail. Experiments on a Scania test vehicle show the advantages and some of the challenges with the proposed approach.

Place, publisher, year, edition, pages
2007.
Keyword [en]
road grade estimation, digital maps, GPS, Kalman filter, sensor fusion
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-81219DOI: 10.3182/20070820-3-US-2918.00010Scopus ID: 2-s2.0-79961098024OAI: oai:DiVA.org:kth-81219DiVA: diva2:497247
Conference
5th IFAC Symposium on Advances in Automotive Control (2007)
Note
QC 20120216Available from: 2012-02-16 Created: 2012-02-10 Last updated: 2012-02-16Bibliographically approved

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Johansson, Karl Henrik

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Sahlholm, PerKozica, ErminJohansson, 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