Modelling the Diverse Implications of Autonomous Mobility at the City Scale

The automation of urban transportation systems has the potential to significantly impact the human experience of cities. Autonomous vehicles (AVs) - from private cars, to shared taxis, and buses - promise improved traffic efficiency and road safety yet raise questions around their effect on the urban realm and the changing nature of human-vehicle interaction. The implementation of wholly autonomous mobility systems furthermore presents policy challenges in relation to access, design, and vehicle ownership. This PhD project will take on these broader implications of autonomous mobility, using agent-based modelling (ABM) to explore the spatial, social, and policy implications of AVs at the urban scale.

The first phase of the research will be to define a set of scenarios for autonomous mobility. The nature of AVs means these scenarios might range from conventional perspectives to quite radical new visions on urban mobility. This project will address how these different planning and policy scenarios might manifest in different outcomes for the city. The scenarios space might include the following, but will be more formally sketched out during the first year of study:

- Vehicle ownership models (e.g. shared, personal).
- Autonomous multimodal mix, including different visions for integration and segregation, and the role of future modes (e.g. personal aviation).
- Multimodal, integrated ticketing and payment systems (i.e. Mobility as a Service).
- Constraints and pricing on vehicle use either applied zonally, by mode, or other means.
- Policy measures targeted at specific populations.

The second underpinning theme of the PhD will be a set of evaluation measures that capture the implications of AVs on urban systems and society. During this stage it will be important to consider the wide-reaching effects of autonomous mobility on established social systems. Again, we are interested in both conventional and radical perspectives on these implications. In relation to the varying system configurations described above, these implications might include:

- Changes in spatial flows, traffic density, and demand for parking.
- Changes in service performance and travel times, differentiated by population characteristics (e.g. by demographic group, deprived populations).
- Displacement of vehicle emissions and environmental burdens.
- Changes in accessibility to different locations, services, and opportunities (e.g. health, education, commerce) brought on by mobility system changes.
- Changes in the experienced city, including the impact on community cohesion, tranquillity, happiness, and so on.

These models of mobility will be constructed using agent-based modelling, which will enable the exploration of scenarios at fine spatial and population scales. Within an ABM in place, in partnership with stakeholder, we will explore policy and urban design solutions aimed at maximising the benefits of autonomous mobility for the city and its citizens. By building ABMs of mobility at the urban scale, innovative solutions towards the inherent computational challenges can also be expected to be an output of the research.

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).