Advanced Driving Simulator

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.


Intention-aware cooperative driving behaviour model for automated vehicles

Developing and evaluating a theoretically grounded novice driver education program incorporating simulators

PhD Research: A new model for human behavioural adaptation in distracted driving

Ability to absorb information through electronic and static signs

Risky Gadgets to the Rescue: Designing Personal Ubicomp Devices to Foster Safer Driving Behaviours in Young Males

CoopEcoSafe: A new cooperative, green and safe driving system

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.


Kazemzadehazad, Sanaz, Monajjem, Saeed, Larue, Gregoire S., & King, Mark J. (2019) Evaluating new treatments for improving driver performance on combined horizontal and crest vertical curves on two-lane rural roads: A driving simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 62, pp. 727-739.

Vaezipour, Atiyeh, Rakotonirainy, Andry, Haworth, Narelle, & Delhomme, Patricia (2019) A simulator study of the effect of incentive on adoption and effectiveness of an in-vehicle human machine interface. Transportation Research Part F: Traffic Psychology and Behaviour, 60, pp. 383-398.

Vaezipour, Atiyeh, Rakotonirainy, Andry, Haworth, Narelle, & Delhomme, Patricia (2018) A simulator evaluation of in-vehicle human machine interfaces for eco-safe driving. Transportation Research Part A: Policy and Practice, 118, pp. 696-713.

Larue, Gregoire S., Blackman, Ross, & Freeman, James (2018) Impact of waiting times on risky driver behaviour at railway level crossings. In 20th Congress International Ergonomics Association (IEA 2018), 26-30 August 2018, Florence, Italy.

Larue, Gregoire S., Wullems, Christian, Sheldrake, Michelle, & Rakotonirainy, Andry (2018) Validation of a driving simulator study on driver behaviour at passive rail level crossings. Human Factors: The Journal of the Human Factors and Ergonomics Society, 60(6), pp. 743-754.

Kim, Inhi, Larue, Gregoire, Ferreira, Luis, Rakotonirainy, Andry, & Shaaban, Khaled (2018) Driver behaviors at level crossings from fixed and moving driving simulators. Procedia Computer Science, 130, pp. 103-110.

Steinberger, Fabius, Schroeter, Ronald, Foth, Marcus, & Johnson, Daniel M. (2017) Designing gamified applications that make safe driving more engaging. In Proceedings of CHI 2017: Conference on Human Factors in Computing Systems, ACM SIGCHI, Denver, Colorado, USA, pp. 2826-2839.

Oviedo-Trespalacios, Óscar, Haque, Md. Mazharul, King, Mark, & Washington, Simon (2017) Self-regulation of driving speed among distracted drivers: An application of driver behavioural adaptation theory. Traffic Injury Prevention, 18(6), pp. 599-605.

Oviedo-Trespalacios, Óscar, Haque, Md. Mazharul, King, Mark, & Washington, Simon (2017) Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers. Accident Analysis and Prevention, 101, pp. 67-77.

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 Sebastien Demmel: or +61 7 3138 7783.