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Taking Representative Samples of Bituminous Binders From Road Tankers from Sampling Points Only
This work tip provides guidance on binder sampling to ensure that consistent and reliably representative samples are obtained so that any test results: represent, as near as practicable, an average of a consignment or batch
Mobile Driver Licences: Developing a Harmonisation Roadmap
This report is an output of a project that incorporated both consultative and desktop research components to establish supportable national policy directions to inform the development of a national mobile driver licences (mDL) implementation roadmap.…
Webinar: Minimum Requirements for Traffic Signs, Traffic Signals and Line Markings
Join us for a webinar that delves into the latest on connected and automated vehicles (CAVs) and the pivotal role that interaction with physical infrastructure plays in their integration into our transport system. In this session, we will present a…
Webinar: Australia and New Zealand Roads Capability Analysis 2022-2032
Following previous workforce capability studies undertaken in 2006, 2009, 2013 and 2017, Austroads engaged Oxford Economics Australia to undertake a new workforce capability analysis for member authorities based on planned and forecasted…
Australia and New Zealand Roads Capability Analysis 2022-2032
This report evaluates the skills and capabilities required by Austroads member agencies in the next decade to achieve their service objectives. It compares these requirements with the current and projected future workforce, identifies potential…
Webinar: Development of Machine Learning Decision Support Tools for Pavement Asset Management
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…
Webinar: Success Strategies for Delivering Artificial Intelligence and Machine Learning Projects
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…
Webinar: Passenger Cars and other Non-Truck Tyres Crumb Rubber in Asphalt
This webinar focuses on the Austroads report Passenger Cars and other Non-truck Tyres Crumb Rubber in Asphalt: National Market Analysis, Review of Industry Practices and Technology Transfer. The report provides a comprehensive overview of the fate…
Development of Machine-Learning Decision-Support Tools for Pavement Asset Management
This report explores the use of Artificial Intelligence (AI) and Machine-Learning (ML) in pavement asset management and details a methodology for developing new use-cases. While there are some existing uses of AI and ML technology in pavement asset…
Passenger Cars and other Non-truck Tyres Crumb Rubber in Asphalt: National Market Analysis, Review of Industry Practices and Technology Transfer
This report provides a comprehensive overview of the fate of end-of-life tyres, the tyre recycling industry in Australia and New Zealand, the specifications for the use of crumb rubber in road applications and the potential benefits of other-than-…