Publications

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.…

This report details road and transport safety interventions that can reduce fatal and serious injury crashes in regional and remote areas. It contains the factsheets, prioritisation framework, and evaluation framework from the report Practical…

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…

This report identifies and discusses physical infrastructure practices that Austroads member agencies could change to improve connected and automated vehicle (CAV) support. It incorporates a review of previous Austroads publications that…

These guidelines set out criteria that must be addressed in any application for an automated vehicle trial. The guidelines aim to provide clear guidance on matters that should be addressed by trialling organisations as part of the trialling process…

This report details road and transport safety interventions that can reduce fatal and serious injury crashes in regional and remote areas. A literature review expands on the Austroads National View on Regional and Remote Road Safety report by…

These guidelines set out the key stages associated with evaluation and reporting of automated vehicle trials including: scoping and planning

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…

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…