Extended Reality for Autistic Drivers (XRAD)

Autistic people generally have lower levels of independence, employment, and quality of life than their non-autistic counterparts. There have been widespread calls to address these imbalances, both from major inter-government organisations (e.g., the UN, NHS, WHO) and community-based advocacy groups. While improvements in these areas can often be achieved through environmental modifications, barriers can arise when autistic people find certain skills difficult to learn or perform. A prominent example here is driving: indeed, studies have shown that autistic people often experience wide-ranging challenges when driving a car and that they are less likely to obtain a license than their neurotypical peers. These skill-related difficulties are strongly linked with reduced personal independence and restricted access to social and/or employment resources. This project will extend my ESRC-funded PhD and subsequent postdoctoral work to address these challenges, by building new evidence-based support tools that enhance driving abilities in autistic people.

To achieve our objectives, the research will build upon three core pillars:

1) Immersive Technologies. Extended Reality (XR) can create highly realistic yet controlled driving simulations that allow learners to practice in an immersive and safe way. Our research suggests that XR can be a particularly promising tool for autistic people, as it can provide engaging learning experiences that are sensitive to diverse individual needs. The proposed work will advance these findings, by researching how XR simulations can be best designed to support autistic people. In collaboration with industry specialists, we will develop a novel, open-source XR application that can enhance autistic driving abilities.

2) Participatory Action Approach. The project will be directly guided by stakeholders from the wider autistic community. Here neurodivergent people will not just be involved as 'subjects', but will meaningfully shape our research aims, methodologies, and conclusions in a series of co-creative workshops and 'idea generation' activities. By interactively working alongside academics, industry specialists and service providers, stakeholders will help co-design the XR tool and decide how it can be effectively applied to meet the needs of neurodivergent individuals and drive positive social change.

3) Neuromotor Science. Research suggests that autistic people process sensory information fundamentally differently from non-autistic people when performing motor tasks. These inherent differences could relate to wide-ranging neuropsychological atypicalities and can explain why autistic people find it challenging to learn practical skills like driving. My PhD shed light on why 'sensorimotor' abilities differ in autistic people and how practical skills could be improved in future learning programmes. Specifically, my results suggested that practitioners should make uncertain and volatile sensory environments feel more predictable during learning. We have since developed novel adaptive XR software, which automatically adjusts simulation features based on real-time user data. The proposed project will incorporate these state-of-the-art adaptive capabilities into a bespoke driving application, so that levels of predictability can be tailored according to a person's unique learning response.

Once these co-creative research developments have been completed, we will conduct an experimental trial that evaluates the validity, feasibility, and initial efficacy of our XR driving tool in autistic populations. The study will use mixed-methods analyses that are based on an established scientific framework for simulation training. The data will provide an empirical, pre-implementation assessment for the XR tool and will be shared with academics, industry specialists, policymakers, and community groups. It will also provide a crucial foundation for my long-term research ambitions.