Safely introducing CAVs into integrated transport networks
Research into customer-focused safe operation of CAVs in various urban environments to improve road user safety & inform NSW of road readiness for CAVs.
Research into customer-focused safe operation of CAVs in various urban environments to improve road user safety & inform NSW of road readiness for CAVs.
Download the three final reports from iMOVE’s ‘Ipswich Connected Vehicle Pilot (ICVP) project.
Download the three final reports from iMOVE’s ‘Improved network performance prediction through data-driven analytics and simulation’ project.
Download a copy of our project final report, ‘Exploring balance between movement and place in designing safe and successful places’.
Watch the recording of our ‘Digitisation of transport and freight: How are we tracking in Australia, and where are the opportunities?’ webinar.
Download the final report from iMOVE’s ‘Digitisation in transport and freight: Lessons for Australia’ project.
This project’s evidence-based approach will allow Main Roads Western Australia’s improvement of roundabout modelling practice and guidelines.
This project will provide comprehensive driving data and analysis tools for the design and testing of an autonomous vehicles software stack.
A study of the attraction/retention of businesses/households to regional cities, & the long-term impacts of COVID on spatial patterns of employment/settlement.
This project will investigate likely contributing factors for traffic crashes involving traffic signal posts in Queensland, and strategies to mitigate these collisions.
Our ‘Encouraging continuation of work from home post-pandemic’ project has been completed, and the final report is available here.
This project will create a model for estimating delays at Perth’s traffic signals, which would inform project decisions and operational strategies.
This project investigates the use of an integrated package of IoT, computer vision and machine learning to support smart bridge health monitoring and 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.
In this PhD project data analytics on Bluetooth trajectories and traffic states will be applied to empirically estimate the assignment matrix for the network.
This PhD project aims to develop a system with a data-driven human driver behaviour model that can help detect the attention level of drivers.