Advanced data analytics: Real-time demand calibration/prediction
This project aims to improve travel demand calibration and accuracy of 24 hour/ 7 days network simulation models for any hour of any day.
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.
Real-time network prediction and response simulation
This project will see an Aimsun Live pilot system installed in Queensland, providing real-time simulation-based prediction, projecting 60 minutes ahead.
Modelling perimeter controls: Detailed simulation
This project will build on simulations of gating, and use MFDs to demonstrate its benefits in enabling better control of the Perth road network.
Transport predictive solution Stage 1: Aimsun WA Live pilot
R&D of new algorithms to process raw data generated by the current RT4 radar, assigning an Austroads classification to all detected vehicles.
Next-generation integrated traffic control
PhD research, developing a new algorithm for integrated traffic network control, with ramp metering, variable speed limit and arterial intersection control.
Aimsun Auto: Model automated vehicles at city scale
Aimsun Auto enables the creation of virtual testing testing environments for the design & validation of path planning algorithms for self-driving vehicles.