Publications

Over the last decade there has been a trend by a number of governments to invest more heavily in transport infrastructure and systems, and to accelerate programs of work. This has been a response to various ‘burning platforms’ including transport…

This report provides practical advice and examples of ways to successfully accelerate transport infrastructure projects and programs up to $500 million. An accelerated project or program has delivery expedited, typically in response to external…

This document provides a hyperlinked list of the Austroads Test Methods and Specifications.

This method has been developed for extracting bituminous binders from bituminous mixtures i.e. asphalt field samples, loose plant mix or reclaimed asphalt pavement.

The test method sets out the procedure for the determination of viscosity of binders recovered from RAP source materials, as well as of virgin binders and rejuvenators.

This test method is used to measure the ability of a concrete with a maximum coarse aggregate size of 20 mm or less to retain its water under pressure. This test determines the amount of water de-filtered when concrete is subjected to a certain…

Austroads Technical Specification ATS 5341 sets out the requirements for the repair of cracks in concrete, including supply and quality of materials, surface preparation, application, relevant testing and acceptance criteria. The technical…

The webinar showcases the projects recognised with the Austroads Bridge Awards. The Austroads Bridge Awards acknowledge individuals and organisations that have delivered outstanding bridge structures and design across Australia and New Zealand. The…

This is the second webinar in a two-webinar series. The session describes two case studies in the use of machine learning (ML) and artificial intelligence (AI) to create decision-support tools for pavement asset management. In the first study, we…

Austroads has published practical guidance to help expand the use of artificial intelligence (AI) and machine learning (ML) in pavement asset management. AI/ML projects are notoriously prone to failure, including late or incomplete delivery, or even…