Chair in Empathic Machines

The Chair in Empathic Machines project, in collaboration with Seeing Machines Pty Ltd and led by Professor Ronald Schroeter, is dedicated to advancing automated vehicle technology that understands and responds to human emotions, intentions, and needs. This initiative aims to enhance safety and cooperation between humans and automated systems, particularly in Conditional Automated Driving scenarios where human intervention is occasionally required.

The project focuses on:

• Understanding links between driver engagement and safety performance in L2-L4 automated driving environments.
• Developing measures to assess and profile driver engagement over time.
• Investigating the interaction between driver engagement, situational awareness, and risk.
• Exploring the role of vehicle occupants in maintaining driver attention.
• Designing Human Machine Interface (HMI) techniques to effectively share attention between driver and vehicle.

Collaborative Research

This multidisciplinary research brings together expertise from various QUT faculties and centers, including:

• Centre for Robotics: Innovations in robotic systems and automated driving.
• Centre for Data Science: Advanced data processing and analysis techniques.
• Centre for Vision Science: Insights into human visual perception in automated driving contexts.

Research and Development

The project includes several targeted PhD projects:

• Human Behavior Analysis: Investigating driver behavior within automated vehicles.
• HMI Design: Developing responsive interfaces based on driver state detection.
• Machine Learning and Robotics: Enhancing automated driving systems using human behavior data.
• Data Science: Managing and analyzing data from vehicle sensors to understand driver behavior better.

Practical Applications

The research leverages the RACQ-owned test track at Mount Cotton, providing a controlled environment for conducting bespoke experiments. This practical approach ensures that the developed technologies are rigorously tested and validated in real-world scenarios.

Media

PhD support needed for AI-human partnership on the road