HMI design to manage attention in automated vehicles (PhD scholarship)

Application dates

Applications close

31 March 2024

What you'll receive

You'll receive a stipend scholarship of $30,000 per annum for a maximum duration of 3.5 years while undertaking a QUT PhD. The duration includes an extension of up to 6 months (PhD) if approved for your candidature. This is the full-time, tax-free rate which will index annually. The PhD project is linked with industry partner Seeing Machines Pty Ltd, so you may be eligible to apply for a stipend top-up via the National Industry PhD Program.

If you're an international student, you will also receive a tuition fee sponsorship for your research degree.

As the scholarship recipient, you will have the opportunity to work with a team of leading researchers, to undertake your own innovative research in and across the field.

Eligibility

How to apply

Apply for this scholarship at the same time you apply for admission to a QUT research degree / Doctor of Philosophy.

The first step is to email Professor Ronald Schroeter detailing your academic and research background, your motivation to research in this field and interest in this scholarship, and include your CV.

If supported to apply, you will then submit an Expression of Interest (EOI) following the advice at How to apply for a research degree. In your EOI, nominate Professor Ronald Schroeter as your proposed principal supervisor, and copy the link to this scholarship website into question 2 of the financial details section.

About the scholarship

We are seeking a highly motivated and talented Vision Science and Human Factors PhD Researcher to join an interdisciplinary research project, conducted in collaboration with Queensland University of Technology (QUT) and industry partner Seeing Machines—world leader in human-machine interaction and an industry leader in artificial intelligence (AI), that enable machines to see, understand and assist the people who are using them.

The project aims to advance the understanding of human behaviour during automated driving, with a strong focus on eye, gaze, and head tracking using Seeing Machines’ optimised driver monitoring system technology. The new knowledge is expected to inform novel strategies that contribute to the safe introduction of Automated Vehicles.

Responsibilities

• Conduct comprehensive literature reviews to understand the current state of HCI/HMI research, focusing on driver engagement and attention sharing in autonomous driving contexts.
• Design and develop novel techniques and interfaces for monitoring and assessing driver engagement in L2-L4 driving environments.
• Collaborate with interdisciplinary research teams from QUT and Seeing Machines to integrate findings from other PhD projects into the broader research objectives.
• Work closely with industry partner Seeing Machines to gain insights into driver monitoring systems and leverage their expertise in interface design.
• Conduct empirical studies to evaluate the effectiveness of different HMI designs in sharing attention between drivers and autonomous systems.
• Analyze qualitative and quantitative data obtained from user studies to gain insights into user behavior, preferences, and challenges.
• Contribute to the development of guidelines and best practices for designing intuitive and effective HMIs in autonomous vehicles.
• Collaborate with other PhD researchers to support interdisciplinary learning and foster a cohesive research environment.
• Publish research findings in high-impact journals and present at relevant conferences and workshops.
• Contribute to the preparation of research reports, project documentation, and funding proposals.
• Engage in regular progress reporting and participate in supervision and mentoring activities.

Qualifications and Skills

• A Master's degree (or equivalent) in Human-Computer Interaction, Human Factors, Cognitive Psychology, or a related discipline.
• Strong research background in HCI/HMI, interface design, cognitive psychology, or a relevant field.
• Familiarity with research methods in HCI, including user-centered design, usability testing, and user experience evaluation.
• Proficiency in design and prototyping tools such as Adobe XD, Sketch, or similar software.
• Experience in conducting empirical studies involving user participants, preferably in the field of human-automation interaction.
• Knowledge of driver monitoring systems and their applications in automated driving is desirable.
• Strong analytical and problem-solving skills, with the ability to translate user insights into actionable design recommendations.
• Excellent communication skills, both written and verbal, for presenting research findings and collaborating with interdisciplinary teams.
• Ability to work independently and as part of a team, managing multiple tasks and priorities effectively.
• Demonstrated publication record (or potential) in peer-reviewed conferences or journals is advantageous.