ONEPlanet DTP - Designing Electric vehicle Commuter travel ENvironments for fuTure LifestYles (DECENTLY) (OP2107)

As a means to mitigate impending climate change and air quality issues associated to transportation emissions, the UK is set a target for 60% of new cars to be electric vehicles (EVs) by 2030. Given the UK population is projected to reach 70 million over this period, it will put immense pressure on the public to adapt to electrical energy usage and commuting patterns for achieving win-win for air quality and climate change. Our currrent research (Bell et al., 2013; Dissanayake, 2017; Ali et al., 2018), together with others (Chapman, 2007; Marsden and Rye, 2010), emphasises the need for radical changes to the way we travel to mitigate climate change issues. This requires deeper understanding of the outlook of British public to future travel.
The British Social Attitudes survey on Climate change has gathered extensive data on to what extent people in Britain believe humans cause climate change, think it is a problem, and feel that citizens and governments are likely to be able to reduce it. However, given the hostility of the population to giving up private vehicles, or moving away from rural areas, a package of measures can only be designed based on a fundamental understanding of the-day-to day activities of people, their travel choices, attitudes towards the environment.
The DECENTLY project focuses on NERC key research area of Environmental Informatics within broader scope of Tools, Technology and Methods, mainly aiming to develop understanding on environmental issues, problems related to energy consumption, through modelling, interpretation, display and dissemination of data and information. Therefore, this PhD will focus on Climate & Climate Change and Environmental Informatics.
Preferred methods
The project will build on a critical state-of-the-review, data mining (mainly DfT data sources), statistical learning, and knowledge discovery of existing comprehensive data to create a fit-for-purpose model. The following will be the main tasks conducted, largely through numerical modelling of existing data:
1. Time series analysis using statistical methods and neural networks to explore the influence of lifestyles & demographics on travel choices over time.
2. Data clustering using Bayesian inference to investigate the effects on behaviours and lifestyles of stimuli (technology, ICT, economy) and policy over time for different sub-groups of population.
3. Cohort analysis to create models to inform mobility policy appropriate to segments of the population.
Links to other research projects/industrial partners
This project will collaborate with industrial partners including DfT (EV data), Newcastle City Council (Air Quality), and NECA (strategic policy), to draw on existing strategies and policies being implemented by them. These will be used to assess the potential and feasibility of such plans to achieve the UK Air Quality targets. In addition, outputs from recently completed PhD research (Dr Fazi Ali) will be used as the initial ground work related to this research (for example, datasets, computer programmes, as well as the findings from her research).