Sharing the Road: Exploring transitions away from private vehicle ownership through agent-based modelling

Emissions from private vehicle ownership are a major contributor to air pollution in cities worldwide. In the UK, private vehicle ownership has been stable for some time, and even increased in years prior to the pandemic (DfT, 2022), with factors such as inadequate public transport, established land use and urban forms, and personal preference all contributing to the maintenance of this trend. The need for flexible and easily accessible private transport is of fundamental importance for many people, particularly those with disabilities, support requirements, or work-related uses. However, private vehicles are a significant issue from an emissions perspective, in contrast to active and shared travel modes. And in the context of local and national targets on achieving Net Zero carbon emissions, navigating a course that balances mobility needs and preferences, with transitions away from private modes is highly pertinent.
There remains considerable uncertainty around the future of transportation, and the future of work, and any consideration of future mobility scenarios must build on prospective attitudes and perspectives. We can build insights here by integrating attitudinal variations in private vehicle ownership and future transportation scenarios with demographic variables, to create predictions of mobility demand transitions. The focus of this study will consider how different models of shared autonomous vehicle service can meet travel demand within the North of England region. Shared AVs have the potential to replace some aspects of private vehicle use, but work needs to be done around establishing the spatiotemporal patterns of those demands, and the feasibility of meeting them.
We envisage four stages to this project.
1. Synthesise current literature around perceptions, attachments, and needs in relation to private vehicle use, and the potential for transition to shared autonomous vehicles. Develop and undertake a survey to collect data on missing or poorly understood facets of mode choice in relation to private and shared modes, with a focus on the Northern England region of interest.
2. Develop a spatial propensity model for uptake of the new mobility service, based on theories of behaviour change, incorporating aspects of demographics, worldview, and mobility need (as identified within the survey study). This part of the work will use microsimulation to scale up survey responses to population scale.
3. Building on the pre-existing CoSMoNorth agent-based transportation model, extend the simulation to incorporate social processes around adoption of new services, building choice models that incorporate the propensity modelling, and technical processes on the optimised delivery and scheduling of the shared autonomous vehicle service.
4. In partnership with stakeholders, develop a set of case studies that explore the delivery of shared autonomous vehicle services, with an exploration of different assumptions around uptake and different service design parameters. The modelling will address issues of service evaluation, generating estimates of changes in travel cost and emissions, as well as secondary impacts on aspects including social equity, urban design, and land use.
The PhD project will interface with and benefit from the vast array of research into agent-based modelling, urban analytics, and future mobility ongoing in the School of Geography, Institute for Transport Studies, and Leeds Institute for Data Analytics (LIDA).