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The Empathic Machines project is the result of a QUT industry collaboration with international driver monitoring systems provider and long-standing Centre for Accident Research and Road Safety – Queensland (CARRS-Q) partner, Seeing Machines Pty Ltd.

A cross-section of QUT faculty schools and disciplines will be brought together to progress the empathic capabilities of automotive AI systems at a time of great change in the automotive industry.

CARRS-Q Principal Research Fellow, Professor Ronald Schroeter, has been appointed The Seeing Machines Chair in Empathic Machines for the initial two-year agreement and is currently recruiting four PhD student positions and one post-doctoral candidate to help deliver the research programs.

“At QUT we have carefully designed PhD projects to span diverse disciplines,” Professor Schroeter said.

Co-contributions from the faculties of Health and Engineering, and three QUT centres: Centre for Robotics; Centre for Data Science; and Centre for Vision Science, will assist with research support, while access to the RACQ-owned purpose-built test track at Mount Cotton will allow bespoke experiments to be conducted.

“The motivation behind this research is to make automated vehicles safer for people especially in this intermediate level where cars are not fully automated,” Professor Schroeter said.

“With Conditional Automated Driving, cars can’t drive everywhere by themselves and will need occasional help from humans and be able to cooperate with them effectively. The basis of any great collaboration is trust and mutual understanding. This is where the empathic machine concept comes in.”

Each PhD project will look at a different aspect of the research:

• Human behaviour within automated vehicles will be examined as part of the vision science project in collaboration with Professor Joanne Wood and Associate Professor Alexander Black.
• The HMI design project will determine the empathic response once the driver’s state has been detected, led by Professor Ronald Schroeter.
• The robotics or machine learning project, in collaboration with Professor Michael Milford from the School of Electrical Engineering and Robotics and Professor Sebastien Glaser from the School of Psychology and Counselling, will use human behaviour data to find ways to improve the automated driving system.
• And the data science project, with Professor Ashish Bhaskar in the School of Civil and Environmental Engineering, will look at how different data sets from the vehicle sensors and Seeing Machine’s Driver Monitoring System can be processed, managed, analysed, and visualised to advance an understanding of driver behaviour during automated driving.

“This is very multi-disciplinary, using university-wide Centre expertise to make this a successful Chair program,” Professor Schroeter said.

Seeing Machines Chief Science & Innovation Officer, Professor Mike Lenné, said the partnership would provide valuable insights into human behaviour as in-vehicle technologies are developed.

"We are delighted to be partnering with QUT on the Chair of Empathic Machines, a critical collaboration to ensure that in-vehicle technologies are developed and implemented safely. Our approach to driver and occupant monitoring is uniquely based heavily on human behaviour and we look forward to being able to leverage the outcomes of this initiative to continue our leadership position in this space and achieve our vision of getting people home safely."

Successful applicants will have an honours degree or equivalent, with backgrounds in psychology, vision science, computer science, HMI, data science, data-based management, machine learning, or robotics.

For more information contact Professor Ronald Schroeter.

Top Picture: Professor Ronald Schroeter with Dr Fabius Steinberger behind the wheel.

 

Media contact:
Debra Bela, QUT Media, 0412 417 552, debra.bela@qut.edu.au
After hours: 0407 585 901 media@qut.edu.au