Funded by the Australian Research Council, QUT, University of Queensland, Department of Transport and Main Roads, RACQ, Motor Accident Insurance Commission, and General Motors Holden, CARRS-Q’s driving simulator incorporates a complete Holden Commodore vehicle with working controls and instruments. The advanced driving simulator uses SCANeR™ studio software with eight computers, projectors and a six degree of freedom (6DOF) motion platform that can move and twist in three dimensions. When seated in the simulator vehicle, the driver and passengers are immersed in a virtual environment that includes a 180 degree front field of view, simulated rear view mirror images, surround sound for engine and environment noise, real car cabin and simulated vehicle motion.
What types of research does it benefit?
The simulator can be used for any form of research which requires an understanding of driver behaviour, including impaired driving, road conditions and environment, the testing of in-car technology and devising methods to protect at-risk road users (e.g. older drivers, young novice drivers). The simulator also allows reproducing and studying risky driving situations without endangering the life of drivers.
Using the Advanced Driving Simulator for research & training
CARRS-Q’s simulator is available for use by researchers and industry through contract or collaborative arrangements.
The Centre provides a venue for researchers to execute their scenario on a driving simulator at several levels of fidelity, ranging from very high (6DOF motion, 180° visual, real car cabin) to medium or low fidelity (desktop). Virtual Reality support is also possible.
Filtness, Ashleigh, Beanland, Vanessa, Larue, Gregoire s, & Hawkins, Alana (2017) Sleep loss and change detection: a driving simulator study. In Tenth International Conference on Managing Fatigue, 20-23 March 2017, San Diego, US.
Haque, Md. Mazharul, Ohlhauser, Amanda D., Washington, Simon, & Boyle, Linda N. (2016) Decisions and actions of distracted drivers at the onset of yellow light. Accident Analysis and Prevention, 96, pp. 290-299.
Larue, Gregoire S., Rakotonirainy, Andry, & Haworth, Narelle L. (2016) A simulator evaluation of effects of assistive technologies on driver cognitive load at railway level crossings. Journal of Transportation Safety & Security, 8(Supplement 1), pp. 56-69.
Haque, Md. Mazharul, Oviedo-Trespalacios, Óscar, Debnath, Ashim Kumar, & Washington, Simon (2016) Gap acceptance behavior of mobile phone distracted drivers at roundabouts. Transportation Research Record, 2602, pp. 43-51.
Dr Sébastien Demmel: email@example.com or +61 7 3138 7783.