AI-powered data dashboard for cycling safety and planning
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.

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.
Outcomes and final report from a project that investigated adoption, perception, and safety aspects of connected and autonomous vehicles on Australian roads.
This project focused on utilising crowd-sourced data for generating road safety insights, aimed to understand the capabilities of such data by developing two prototype applications for road infrastructure managers.
This project leverages drone video analytics data collected at over 50 roundabouts in Perth to conduct comprehensive safety analyses.
This project will look to replace subjective assessments of ADAS (Lane Departure Warning and Lane Keep Assist) with empirical metrics.
This project provided an overview of new and emerging technology solutions to aid community engagement around road safety.