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 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…

This report presents an agency business capability model to support connected vehicles. The model defines the required agency business capabilities and associated capability maturity target states from business and technology perspectives. Connected…

This report is an addendum to the Austroads Future Vehicles 2030 report (AP-R623-20), published in June 2020. Future Vehicles 2030 included forecasts of sales and fleet penetration for eight vehicle technologies or uses, including Automated Driving,…

This report provides an evaluation framework, practices and supporting tools for evaluating road preservation and renewal treatment options for predominantly sprayed seal flexible pavements. It includes a compilation of case studies based on a…

This report details research undertaken to improve the mechanistic-empirical procedure for pavement rehabilitation and strengthening treatment design included in Austroads Guide to Pavement Technology Part 5: Pavement Evaluation and Treatment Design.…

This report identifies and evaluates technology solutions that meet asset management needs relating to road pavement performance. The increasing pace of change of technology brings considerable promise of more data, of a higher quality, captured for…

Australian and New Zealand vehicle fleets may be entering a period of significant change due to the emergence of Automated, Connected and Electric Vehicles and new models of vehicle ownership and use such as ride sharing services. This report…

An existing model predicted binder life by combining a binder hardening (increase in viscosity) model and a distress viscosity model. Inputs for the two models were site temperature parameters, binder durability (resistance to hardening) and seal…

An existing model predicted maximum seal life by combining a binder hardening (increase in viscosity) model and a distress viscosity model. Inputs for the two models were site temperature parameters and binder durability (resistance to hardening).…