Model-based winter road classification

被引：17

作者：

Casselgren, Johan ^{[1
]}

Sjödahl, Mikael ^{[1
]}

LeBlanc, James P. ^{[2
]}

机构：

[1] Division of Experimental Mechanics, Luleå University of Technology

[2] Division of Signal Processing, Luleå University of Technology

来源：

International Journal of Vehicle Systems Modelling and Testing | 2012年 / 7卷 / 03期

关键词：

Ice; Optical sensor; Road friction estimation; Road surface classification; Safety applications; Snow; Vehicle applications; Winter road classification;

D O I：

10.1504/IJVSMT.2012.048941

中图分类号：

学科分类号：

摘要：

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. Copyright © 2012 Inderscience Enterprises Ltd.

引用

页码：268 / 284

页数：16

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