With global urbanisation anticipated to reach 68% by 2050, there is a significant risk of exacerbating urban transport emissions. Urban transport decarbonisation is a complex adaptive system challenge, the understanding and optimisation of which could be supported by digital twins (DTs). Although prior research has explored digital and big data technology applications, creating actionable insights requires human-centred designs. We conducted a structured workshop to gather practitioner views on how urban-scale DTs can support transport decarbonisation. Specifically, we explored the outcomes they aim to achieve, the interventions they are interested in, and the value digital twinning offers compared to current methods. The data was synthesised and analysed to identify (1) impacts, (2) interventions, (3) location types, (4) data sources and (5) feedback mechanisms of importance to participants. These five aspects are proposed as a framework to support the definition of digital twinning use cases targeting urban transport decarbonisation. Application of the framework encourages creators to explicitly consider the services to be provided to users, how the derived insights influence the real world and the data connections between the physical and digital, noting that these are often overlooked in reported research. A framework application is illustrated through an example use case described for the West Midlands, UK.
Steele et al. (Thu,) studied this question.