Understanding perceived safety and travel behaviour in shared spaces
This project will explore how traffic conditions, design quality, and user perceptions interact to influence safety and travel choices.

This project will explore how traffic conditions, design quality, and user perceptions interact to influence safety and travel choices.
An overview of the completed “Mitchell Smart Freeway (Southbound): Live decision support” project, enabling MRWA to exhaustively test response plans.
Using sensors to detect unsafe following distances, the system aims to reduce tailgating by encouraging better behaviour through targeted messages.
An overview of iMOVE’s completed project “Desire lines user behaviour: Initial research”, along expected project impact and downloadable final report.
This project will co-adapt the Pre-learner Driver Education Program for cultural relevance with First Nation communities, and blueprint Indigenous Data Sovereignty.
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.
This project will look to quantify the benefit of the Australian adoption of eCall, a life-saving technology aimed at reducing emergency response times, enabling autonomous contact with emergency services.
Overview and final report of the completed project, “Large Animal Activated Roadside Monitoring and Alert System”. Also recommendations for additional research.
This webinar looked at results and the (safer) road ahead for the Large Animal Activated Roadside Monitoring and Alert System.
Outcomes from the trial of a Level 4 capable autonomous vehicle on public streets in and around the University of Sydney.
This project investigated the most effective traffic control measures to reduce the frequency/occurrence/severity of injuries at end of queue roadwork sites.
iMOVE Australia was at the test track to see technology from its connected motorcycle trail project in action.
This webinar presents the methods, outcomes, and recommendations from the completed “Working near traffic: Work zone end of queue study” project.
This project leverages AI-driven video analytics to improve safety and efficiency for vulnerable road users at Melbourne intersections.
This project will provide evidence to support better decision-making and assessment in planning and designing Transit-Oriented Developments in Perth.
The outcome of this project is expected to yield reliable and consistent incident records, providing accurate statistics and better insights for enhanced decision-making.