Accelerated and intelligent RAP data collection
Use of AI and machine learning techniques in collecting AusRAP data has potential to reduce costs and increase the frequency and accuracy of its information.
Innovative local transport: Community transport of the future
This project will investigate the systemic issues, opportunities, and barriers for overcoming transport disadvantage and enhancing community transport.
Developing empirical customer-centric public transport
This PhD research project aims to assist public transport service providers improve quality, operational efficiency, and farebox recovery ratios.
Strengthening cybersecurity in vehicular networks
This project will develop new highly efficient cybersecurity schemes to reverse engineer vehicular network communications.
IAG student/industry project tackles vehicle cybersecurity issues
A student team from UTS, and staff from IAG’s Research Centre worked together this year on a project involving vehicle cybersecurity.
TRANSW Virtual Symposium 2020, Nov 17—19
The Ipswich Connected Vehicle Pilot sees hundreds of cars fitted with technology to allow them to communicate with each other and with road infrastructure.
Modelling traffic disruption impact: Deep Learning & simulation
This PhD looks at prediction of traffic disruptions in cities using AI and synergising traffic simulation modelling to help traffic authorities respond.
Mina Ghanbarikarekani wins Best Student Paper
Mina Ghanbarikarekani, a PhD student at the University of Technology Sydney, has won the Best Student Paper Award at an international ITS conference.
Cyber security for connected vehicles and vehicular networks
Addressing the critical need for new security schemes to be designed and implemented to protect our connected cars and transport systems.
Green wave for high capacity public transport services
Development of an algorithm to provide priority at traffic lights to public transport, also with potential to reduce stop time for private vehicles.