EPSRC DLA: Understanding preferences and modelling ‘difficult’ choices through virtual reality experiences

One full scholarship is available in the Institute for Transport Studies for 2025/26 entry for a Home fee rated applicant. This is a highly competitive EPSRC Doctoral Landscape Award Studentship offering the award of UK fees, together with a tax-free maintenance grant (currently £19,237 for academic session 2024/25) for 3.5 years. This award is only available to Home fee rated applicants. Training and support will also be provided. Please note that whilst you may be successful in securing an academic offer for this project, this does not mean that you have been successful in securing an offer of funding. Funding is awarded on a competitive basis.<br /> <br /> Many of the activity and travel choices we make involve no right or wrong decisions and the trade-off between the attributes of possible alternatives is very context and person-dependent. For instance, during the COVID-19 pandemic, significant differences were observed around the world and among different ethnic groups in terms of risk-taking propensity which in turn affected the shift in activity and travel patterns throughout this year (Dryhurst et al. 2020). There have also been country-level variations observed in what is the `right’ decision in the so-called `moral machine’ choice setting, where an individual must choose whom to save if an autonomous vehicle (AVs) hypothetically were to crash (Awad et al. 2020). <br /> <br /> ‘Choice models’ are mathematical models designed to predict and forecast which alternative(s) an individual will choose in a given scenario. These models aim to understand the key factors (including cognitive, emotional, and motivational) that lead to different individuals making different choices. However, alongside sensitivity to the factors influencing the choices (e.g. preference differences regarding travel time and cost in the context of travel mode selection), there is also possible differences in the way in which individuals think and make decisions. For example, there have been psychological theories put forward to explain how and why individuals from the East might think differently to those from the West and how this can lead to markedly different choices (e.g. Nisbett 2004). These differences appear to be particularly prominent in the case of `difficult’ decisions where the alternatives could be categorised as `right’ or `wrong’ and/or there is inherent uncertainty in the outcomes of a choice.

<p paraeid="{8e4f7fc1-9927-43e7-808a-d00a0906ef75}{111}" paraid="1545723592">To understand individual preferences, choice modellers have historically relied on stated preference surveys and responses to questionnaires on psychometric scales. These are, however, subject to hypothetical biases and measurement errors, with biases becoming more influential in the case of difficult/risky/moral decision-making, as decision-makers likely do not face the consequentiality of their choices. Additionally, decision-makers may not wish to appear immoral and may attempt to hide their true preferences.  </p> <p paraeid="{8e4f7fc1-9927-43e7-808a-d00a0906ef75}{121}" paraid="1630778075">In our early research in this area, we have demonstrated how physiological data can be used to help understand decision-making. For example, Paschalidis et al., 2018, demonstrated that integrating physiological response data with driving choice data can better capture the effect of stress on driving decisions; Bogacz et al. (2019) demonstrated that using electroencephalogram (EEG) data can help understand risk perception when cycling in a virtual reality (VR) setting. A key advantage of physiological data is that it can sidestep hypothetical biases by providing outputs that cannot be controlled by the decision-maker (i.e. heart-rate). </p> <p paraeid="{8e4f7fc1-9927-43e7-808a-d00a0906ef75}{131}" paraid="1494113176">The aim of this project is to advance this further, both methodologically and empirically, by using physiological data combined with choice data in a wide range of VR representations of real-world scenarios to obtain more reliable forecasts of how individuals respond to risky or moral choice scenarios. This will allow us to better understand human reactions to risky situations with uncertain outcomes which can be useful for artificial intelligence-based policy planning. They can also help to better predict choices involving moral aspects, for example, in travel behaviour (policies to promote the uptake of electric vehicles), energy consumption (encouraging carbon neutrality through carbon offsetting schemes) and beyond.  </p>

<p>Formal applications for research degree study should be made online through the <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University's website</a>. You will need to create a login ID with a username and PIN. <strong>Please follow these instructions carefully or your application may not be considered.</strong></p> <ul> <li>For ‘Application type’ please select ‘Research Degrees – Research Postgraduate’.</li> <li>The admission year for this project is 2025/26 Academic Year.</li> <li>You will need to select your ‘Planned Course of Study’ from a drop-down menu. For this project, you must scroll down and select ‘<strong>EPSRC DLA Environment</strong>’. If you do not apply under this programme code, your application cannot be considered.</li> <li>Please state the funding you wish to be considered for is <strong>EPSRC Doctoral Landscape Award 2025/26: Environment</strong>.</li> <li>The project start date for this project is October 2025, please use this as your Proposed Start Date of Research.</li> <li>Please state clearly in the research information section that the research degree you wish to be considered for is <strong>EPSRC DLA: Understanding preferences and modelling ‘difficult’ choices through virtual reality experiences</strong> as well as <strong>Dr Thomas Hancock</strong> as your proposed supervisor.</li> <li>You must provide the following documents in your application: <ul> <li>Full transcripts of all degree study, or if in final year of study, full transcripts to date</li> <li>Personal statement outlining your interest in the project</li> <li>CV</li> </ul> </li> </ul> <p paraeid="{790021b7-4ac3-44f0-8be8-850148d45e0e}{232}" paraid="490689747">If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below). </p> <p paraeid="{790021b7-4ac3-44f0-8be8-850148d45e0e}{242}" paraid="961643973"><em>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability. </em></p>

Applicants should normally have a bachelor degree with a minimum of 2:1 (Hons) or equivalent in a scientific discipline. Desired skills: (1) Some experience in the use of VR; (2) Some experience in computer programming; (3) Interest in choice and behavioral modelling using Big Data. Applicants who are uncertain about the entry requirements for a particular research degree are advised to contact the Postgraduate Research Admissions team prior to making an application.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<p>This competitive EPSRC Doctoral Landscape Award offers the award of tuition fees at the Home rate, together with a tax-free maintenance grant (currently £19,237 for academic session 2024/25) for 3.5 years. Training and support will also be provided. This award is only available to Home fee rated applicants.</p> <p>Please note that whilst you may be successful in securing an academic offer for any project linked to this funding advertised project or own research proposal, this does not mean that you have been successful in securing an offer of funding. Funding is awarded on a competitive basis.</p> <p>Please refer to the <a href="https://www.ukcisa.org.uk/">UKCISA</a> website for information regarding fee status for Non-UK Nationals.</p>

<p>For further information please contact the Postgraduate Research Admissions team: <a href="mailto:env-pgr@leeds.ac.uk?subject=EPSRC%20DLA%3A%20Promoting%20Healthy%20Ageing%20through%20Diverse%20Mobility%20Options">env-pgr@leeds.ac.uk</a>. </p>