Using 3D Images to Analyse the Microtexture of Aggregates

Skid resistance, whilst being complex, is one of the more controllable factors that road engineers can design and modify to reduce the number of wet pavement and loss of control crashes. However, due to the fact that it deteriorates over time due to polishing and/or abrasion, it is desirable to be able to predict the long term skid resistance performance of aggregates before the road surface is constructed. Skid resistance consists of both microtexture and macrotexture. There are a number of methodologies that have been developed to analyse and quantify the macrotexture of road surfaces and the relationship between skid resistance and macrotexture has been established with reasonable confidence. On the other hand, it is a more challenging task to accurately analyse and quantify microtexture changes due to its microscopic scale. This paper discusses the usage of a new device, namely the InfiniteFocus 3D, which is an optical three-dimensional surface profile measurement system that can be used to generate detailed three-dimensional images of aggregate surfaces at the micro scale. These images can be used to analyse the microtexture of aggregate surfaces by calculating certain surface texture parameters (both manually and, using the associated software, automatically generated by using the associated software). In ongoing research at the University of Auckland, it is intended to assess the predictive power of such parameters in predicting skid resistance deterioration due to aggregate polishing and wear.

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Additional Info

Field Value
Source NZTA 14th Annual Conference
Author Nataadmadja, Adelia, Wilson, Douglas, Costello, Seosamh, Do, Minh Tan
Maintainer CCSD
Last Updated May 7, 2026, 21:46 (UTC)
Created May 7, 2026, 21:46 (UTC)
Identifier hal-00915781
Language en
contributor Department of Electrical and Computer Engineering [Auckland ] (ECE) ; University of Auckland [Auckland]
creator Nataadmadja, Adelia
date 2013-11-03T00:00:00
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harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2023-08-07T00:00:00
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