This project looks at how to inform policy by providing research on uptake rates, locations and use of electric vehicles.
Flexing passenger mobility
Access to flexible transportation is becoming easier as car use rather than ownership is facilitated by new finance and payment mechanisms, smartphone technology, Big Data and ‘on demand’ mobility services. Thinking about flexibility in energy transitions ranges from assuming that current spatial and temporal patterns of energy demand are entirely inflexible to models which imply complete adoption of technically possible flexibility. This project is examining how transport and energy system models can better account for social, spatial and temporal differences in the constraints and opportunities for flexibility. Specifically, it is producing a passenger car vehicle-level classification which is spatially, socially and temporally disaggregated. It is based on conceptualisations of flexibility translated into novel indices to characterise vehicle use based on: intensity, duration, regularity (timing, destinations, and occupancy), sequencing, periodicity, turbulence, temporal rhythms over the week. The results are being used to inform policy by estimating an ‘upper threshold’ to PEV penetration, below which ICEs can be replaced without ‘threatening’ current patterns of use and expectations. They will also allow estimates of the scope for switching to alternative modes, car-relinquishment, and the diffusion of ‘on demand’ services.
Banner photo credit: Christopher Burns on Unsplash
