Transport predictive solution Stage 2: AI and real-time simulation
This project will offer a real-time decision support tool for traffic operations centres to predict network congestion, and evaluate the possible responses.
This project will offer a real-time decision support tool for traffic operations centres to predict network congestion, and evaluate the possible responses.
Read about the findings from our ‘Conceptual architecture for future transport and mobility environment’ project, and download the final report.
This study will look at current Australian attitudes towards CAVs, and levers available for government to increase community acceptance and confidence.
This project will build on simulations of gating, and use MFDs to demonstrate its benefits in enabling better control of the Perth road network.
A project examining the benefits/drawbacks of working from home, and the impacts of different arrangements on productivity, transport, health, & wellbeing.
The results of an eight-month study of the benefits of moving to more connected vehicle technology on Australian roads have been released.
R&D of new algorithms to process raw data generated by the current RT4 radar, assigning an Austroads classification to all detected vehicles.
Research into a network-wide approach to identify critical links and estimate the Macroscopic Fundamental Diagram using flow and density measurements.
Development of demand management & estimation tools for large-scale traffic networks, incorporating macroscopic fundamental diagram-based traffic dynamics.
A project looking at vehicle detection technologies for traffic signal control and smart freeway operations, using comparative analysis and field trials.
Safety and congestion are two of the key challenges on our networks and there is strong potential for connectivity and C-ITS to help.
A feasibility study looking at the possibility of diverting some freight tasks from the road network to utilising spare capacity on public transport.
This project looks to consider current parking challenges, & work towards a solution that enables the wider availability & usability of car-share services.
Improvement of Brisbane’s parking management through analysis, prediction, and data sharing.
Development of an algorithm to provide priority at traffic lights to public transport, also with potential to reduce stop time for private vehicles.
This iMOVE research project involves the collection and analysis of detailed data to implement and validate advanced algorithms, to support the early identification of the onset of congestion and identify how best to mitigate its potential impact.