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.

Austroads extended vehicle classification scheme builds on the influential 1994 scheme. The extended scheme provides greater granularity across the 12 classes in the 1994 scheme. It also provides a new classes for: active transport to address the…

In this webinar, Chris Koniditsiotis, Lead Implementation Consultant and Patsy Thomas, National Temporary Traffic Management (TTM) Operations Manager provide an update on the implementation and operational commencement of the Austroads National…

This report presents a set of reference architecture models, content and guidance for use by road agencies to identify, plan and improve their Multimodal Incident Management (MMIM) capabilities. MMIM is defined as the resolution of an unplanned…

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…