Intelligent Transport Systems

Our research investigates road safety benefits and human factors aspects of future Intelligent Transport Systems technologies. This includes the design, use and assessment of information systems and in-vehicular technologies, as well as their simulation, real-world impact and cost-benefit analysis.

We use the Safe System approach to understand the human factors challenges arising from the introduction of new ITS, such as Connected Automated Vehicles (CAV), e-bikes and mobility services, by focusing on the patterm of cooperation between road users. We capitalise on research progress in the Internet of Things (IoT), automated/connected cars, Deep learning (AI), person’s data acquisition (Quantified Self) and ubiquitous computing to reduce behavioral uncertainties in transport.

Team members have expertise in computer science, civil engineering, psychology, sociology, HMI/HCI, design, mathematics and statistics.

Our research benefits from access to high quality facilities including an Advanced Driving Simulator, research vehicle, in-vehicle sensors and a range of analysis software and in-vehicle sensors. The team collaborates with prestigious road safety centres including IFSTTAR (LIVIC, LPC) and UMTRI as well as Cornell University and Ludwig-Maximilian University of Munich.

Contact:


Professor Andry Rakotonirainy: r.andry@qut.edu.au or +61 7 3138 4683.