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PhD Studentship: Nottingham University Human Factors Research Group PhD

University of Nottingham - Engineering

Qualification Type: PhD
Location: Nottingham
Funding for: UK Students, EU Students, International Students
Funding amount: See advert for details
Hours: Full Time
Placed On: 21st January 2025
Closes: 27th January 2025
Reference: ENG2344

This PhD will primarily comprise empirical simulator studies to investigate the impact of novel vehicle automation technologies on driver behaviour and performance. Novel technologies enable vehicles to drive 'autonomously', i.e. without physical input from a driver (feet on pedals, hands on steering wheel), yet there is an expectation that drivers will need to remain visually attentive to the driving task during this type of automated driving for the foreseeable future. This situation presents a significant Human Factors problem, as humans are poor at remaining visually attentive to a task when physically disengaged from it. UK regulators require empirical evidence of human behaviour and performance in response to eyes-on / hands-off / feet-off automated driving systems (also known as Driver Controlled Assistance or Level 2++ automation). The Human Factors Research Group (HFRG) at the University of Nottingham is well placed to engage directly with UK regulators and decision makers and this research will be responsive to the requirements of these stakeholders during the next 3-4 years, which will be a critical time in CAV (Connected and Autonomous Vehicle) development in the UK. 

The student will join a research team with an established track record in studying human behaviour under different driving conditions, creating bespoke software and hardware scenarios, and collecting data on many aspects of performance including visual attention, workload, situational awareness, etc. The research will comprise a series of simulator studies, using the HFRG's state-of-the-art driving simulator facility. These studies will simulate state-of-the-art CAV technologies in realistic driving situations to capture data from human participants. Empirical work will be complemented with academic review of literature, legislation, design guidelines, etc. to identify research gaps and design methodologies. The PhD outcomes will inform our understanding of how to design, regulate and legislate for future CAV systems with the safety and wellbeing of human users as the primary goal.  

We are looking for an enthusiastic and self-motivated person who meets the academic requirements for enrolment in PhD research at the University of Nottingham. You will have a 1st class or good 2:1 honours degree and/or an MSc in a relevant subject, such as Human Factors / Ergonomics, Applied Psychology, Human-Computer Interaction, UX design, Computer Science. If you are currently working towards an undergraduate or postgraduate degree in a relevant area with predicted grades as above and expected completion date before the end of 2025 then you are also encouraged to apply. The successful candidate will be able to demonstrate an enquiring and rigorous approach to research, together with a strong intellect and disciplined work habits. The candidate will need good team-working, communication and networking skills as they will engage with relevant stakeholders to disseminate findings, as well as manage the recruitment and testing of study participants. Experience of software programming is desirable as the successful candidate will need to develop scenarios using the simulator software package, SCANeR. Experience of designing and implementing successful research methodologies is also useful.  

The PhD position is available to start between 1st October and 1st December 2025. We can consider applications from both UK and international students. 

Informal enquiries may be sent to Dr. Cath Harvey (Catherine.harvey@nottingham.ac.uk). 

If you wish to apply, please send a CV and cover letter (outlining your interest in the topic area and why you think you are a good fit for the position) to Catherine.Harvey@Nottingham.ac.uk, by 5pm 27th January, 2025. 

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