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Model-based winter road classification
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.ORCID iD: 0000-0003-4879-8261
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2012 (English)In: International Journal of Vehicle Systems Modelling and Testing, ISSN 1745-6436, E-ISSN 1745-6444, Vol. 7, no 3, p. 268-284Article in journal (Refereed) Published
Abstract [en]

An investigation of different road conditions has been conducted using a short-wave infrared (SWIR) light online sensor to examine the possibility of estimating road condition parameters such as porosity, depth and roughness. These parameters are essential for non-contact road friction estimation. The investigation show that it is possible to detect changes of depths of water and ice as well as classify different types of ice, by utilising polarised short-wave infrared (SWIR) light and a modified Hapke directional reflectance model

Place, publisher, year, edition, pages
2012. Vol. 7, no 3, p. 268-284
Keywords [en]
Technology - Electrical engineering, electronics and photonics
Keywords [sv]
Väggrepp, Väglagskarakterisering, Väglagsklassificering, Teknikvetenskap - Elektroteknik, elektronik och fotonik
National Category
Applied Mechanics Signal Processing
Research subject
Experimental Mechanics; Signal Processing
Identifiers
URN: urn:nbn:se:ltu:diva-9531DOI: 10.1504/IJVSMT.2012.048941Scopus ID: 2-s2.0-84866262098Local ID: 82f2a1c4-9ec2-48de-ae2a-2e3496ea3d10OAI: oai:DiVA.org:ltu-9531DiVA, id: diva2:982469
Projects
CASTT - Centre for Automotive Systems Technologies and Testing
Note
Validerad; 2012; 20110416 (johcas)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Casselgren, JohanSjödahl, MikaelLeblanc, James

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