Queensland’s Cooperative & Automated Vehicle Initiative (CAVI)
The Department of Transport and Main Roads (Queensland) CAVI initiative is at the forefront of work on connectivity and automation for safer & cleaner roads.
Optimising motorway control algorithms: New technologies/data
This project aims to perform a comprehensive diagnostic of TMR’s motorway control algorithms and opportunities for optimisation using emerging technologies.
Train horns: Broader social effects and pedestrian simulations
This project will complete an investigation of train horn effectiveness, & inform transport industry orgs and policymakers of future procedures and applications.
Using crowdsourced data to improve road management
Demonstrating the use of historic crowdsourced data to create value in road management process by prototyping tools supporting road network management.
Safety risk evaluation of the remote operation of HAVs
This project will identify functional safety risks of selected scenarios of the remote operation of Highly Automated Vehicles, and provide recommendations.
ODIN PASS MaaS trial opportunity for Summit 2022 attendees
Register for our 11 August 2022 webinar, “Hydrogen in transport: Progress and next steps. Speakers from Hyzon, Volvo, and more.
Chintan Advani – iMOVE PhD student
Chintan Advani’s PhD topic is ‘Empirical modelling of traffic states and route choice behaviour’. This profile outlines his work, lessons learnt, and more.
Older drivers: Advanced driving assistance technologies and AVs
This research will address key issues regarding perceptions of ADAS and AVs in older adults, the extent to which this tech can improve their safety and mobility.
Ipswich Connected Vehicle Pilot: Final reports
Download the three final reports from iMOVE’s ‘Ipswich Connected Vehicle Pilot (ICVP) project.
2022 National Forum on Urban Freight Logistics Education
The National Forum on Urban Freight Logistics Education will take place on 17 June, 2022, at QUT and online.
Traffic lights: Collision avoidance strategies/damage mitigation
This project will investigate likely contributing factors for traffic crashes involving traffic signal posts in Queensland, and strategies to mitigate these collisions.
Developing an urban freight planning course: A scoping study
A scoping study to identify opportunities to improve urban freight planning tertiary education in Australia, improving education outcomes for freight logistics.
Brisbane parking management: An integrated, strategic approach
This research will extend over a three-year period and develop a strategic digital plan to improve the parking experience in Brisbane.
Real-time crash risk estimation using machine learning
Using state-of-the-art machine learning algorithms, this study will use a novel modelling approach to accurately predict traffic crashes in real-time.
Scenario developments for forecasting urban freight shifts
This project will develop a framework/tool for forecasting future scenarios of urban freight in informing planning and regulation (transport and land use).
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.