Victor Deville’s PhD project is Non-invasive vehicle classification solution using tracking radar. Read about the project, and his approach to the research.
Watch the video recording of our ‘C-ITS in Australia:’ webinar, plus an invitation to participate in future C-ITS projects.
This project will develop data fusion and machine learning models to estimate service use for Melbourne trams and make real-time prediction of tram loads.
This webinar will look at progress made to date with C-ITS technologies in Australia, and discuss ideas about how we can build on this knowledge.
A downloadable progress report on our Evaluating loading dock capacity in new developments project.
The main aim of this project is to develop a set of effective policy responses for improving the efficiency of delivery operations in the Sydney metropolitan area.
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.
Watch the video of our Insights from COVID-era traffic data webinar Q&A, featuring speakers from Intelematics, TomTom, and the University of Melbourne.
The technology on iMOVE’s project on the AIMES transport test bed is about to have an AI-enabled video system to make its intersections safer.
A PhD research project aiming to build a model/platform using real-time feeds of all mode movements from smart intersections to optimise signal control.
Development of an improved and reliable methodology for forecasting demand to establishing loading dock requirements in new developments.
Safety and congestion are two of the key challenges on our networks and there is strong potential for connectivity and C-ITS to help.
An interview with Majid Sarvi, chair in Transport Engineering, and professor in Transport for Smart Cities at the University of Melbourne.
Australia and the US state of Michigan connected via an MOU this week, looking to share knowledge and expertise in all things Intelligent Transport Systems.
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.