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Vehicle Classification using Road Side Sensors and Feature-free Data Smashing Approach
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Department of Electrical Engineering and Automation, Aalto University.
School of Information Technology, Halmstad University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-5888-8626
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Number of Authors: 6
2016 (English)In: 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC 2016), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016, 1988-1993 p., 7795877Conference paper (Refereed)
Abstract [en]

The main contribution of this paper is a study of the applicability of data smashing – a recently proposed data mining method – for vehicle classification according to the “Nordic system for intelligent classification of vehicles” standard, using measurements of road surface vibrations and magnetic field disturbances caused by passing vehicles. The main advantage of the studied classification approach is that it, in contrast to the most of traditional machine learning algorithms, does not require the extraction of features from raw signals. The proposed classification approach was evaluated on a large dataset consisting of signals from 3074 vehicles. Hence, a good estimate of the actual classification rate was obtained. The performance was compared to the previously reported results on the same problem for logistic regression. Our results show the potential trade-off between classification accuracy and classification method’s development efforts could be achieved.

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016. 1988-1993 p., 7795877
Series
IEEE International Conference on Intelligent Transportation Systems, ISSN 2153-0009, E-ISSN 2153-0017
National Category
Computer Science Control Engineering Signal Processing
Research subject
Signal Processing; Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-59788DOI: 10.1109/ITSC.2016.7795877ISI: 000392215500310ScopusID: 2-s2.0-85010042316ISBN: 9781509018895 (electronic)OAI: oai:DiVA.org:ltu-59788DiVA: diva2:1037576
Conference
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC 2016), Rio de Janeiro, Brazil, 1-4 Nov 2016
Available from: 2016-10-17 Created: 2016-10-17 Last updated: 2017-02-17Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
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