Model-based winter road classification
2012 (Engelska)Ingår i: International Journal of Vehicle Systems Modelling and Testing, ISSN 1745-6436, E-ISSN 1745-6444, Vol. 7, nr 3, s. 268-284Artikel i tidskrift (Refereegranskat) 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
Ort, förlag, år, upplaga, sidor
2012. Vol. 7, nr 3, s. 268-284
Nyckelord [en]
road surface classification, vehicle applications, road friction estimation, optical sensor, safety applications, winter road classification, ice, snow
Nyckelord [sv]
Väggrepp, Väglagskarakterisering, Väglagsklassificering
Nationell ämneskategori
Teknisk mekanik Signalbehandling
Forskningsämne
Experimentell mekanik; Signalbehandling
Identifikatorer
URN: urn:nbn:se:ltu:diva-9531DOI: 10.1504/IJVSMT.2012.048941Scopus ID: 2-s2.0-84866262098Lokalt ID: 82f2a1c4-9ec2-48de-ae2a-2e3496ea3d10OAI: oai:DiVA.org:ltu-9531DiVA, id: diva2:982469
Projekt
CASTT - Centre for Automotive Systems Technologies and Testing
Anmärkning
Validerad; 2012; 20110416 (johcas)
2016-09-292016-09-292022-08-31Bibliografiskt granskad