What can transport do to help increase national productivity?
A comprehensive review of the Australian transport sector, with recommendations improving its efficiency and contribution to national productivity.

A comprehensive review of the Australian transport sector, with recommendations improving its efficiency and contribution to national productivity.
A wrap-up, and downloadable final report, for the competed project “Using real-time train data to improve level crossing safety”.
A wrap-up, and downloadable final report, for the competed project “Optimising motorway control algorithms: New technologies / data”.
A wrap-up, and downloadable final report, for the competed project “Replacement bus patronage counting and wait time measurement”.
A wrap-up of the completed Streamlining and integrating incident data project, in which an AI-powered solution was developed to manage information about road transport incidents in real time.
A project in which 400 See.Sense smart bike lights will collect data for predictive safety insights for transport planners in Sydney and the Victorian Surf Coast region.
Development of an interactive bussing tool to accurately visualise disruptions, quantify customer impacts, and recommend actionable and right size responses.
The outcome of this project is expected to yield reliable and consistent incident records, providing accurate statistics and better insights for enhanced decision-making.
This project focused on utilising crowd-sourced data for generating road safety insights, aimed to understand the capabilities of such data by developing two prototype applications for road infrastructure managers.
This project leverages drone video analytics data collected at over 50 roundabouts in Perth to conduct comprehensive safety analyses.
An innovative low-cost Internet of Things (IoT)-based solution providing real-time insights into freight location and condition, including maintaining cold chains.
This project will develop an innovative traceability system for the Australian Southern Rock Lobster industry, leveraging computer vision and machine learning.
This project will develop a data fusion framework to infer road freight origin-destination flows using information from multiple sources.
A wrap-up of the “Modelling perimeter controls: Detailed simulation project”, including conclusions and directions for further research, and a copy of the final report.
This project’s aim was to improve efficiency of tram operations, assist with route and service planning, integration, and operation of tram routes with other modes of transport.
The project developed a tailored roadmap for the governance of truck movement data for the purposes of informing policy, planning and network operations.