INFUZE: Estimating the potential for shared mobility across place at the national scale

Summary

One full scholarship is available at the School of Geography in 2025/26. This scholarship is open to UK and international applicants and covers tuition fees plus maintenance stipend at the UKRI rate (£19,237 in 2024/25) for three and a half years, subject to satisfactory progress.

This fully funded PhD place provides an exciting opportunity to pursue postgraduate research in a range of fields relating to environmental science and climate change.

The School of Geography invites applications from prospective postgraduate researchers who wish to commence study for a PhD in the academic year 2025/26 for the School of Geography INFUZE scholarship.

The award is open to full-time candidates (UK and international) who have been offered a place on a PhD degree at the School of Geography.

Transitions towards sustainable urban mobility is dependent on a viable set of alternative transport modes being available for citizens. Therefore, understanding how different, and particularly shared modes might contribute to meeting the diverse needs of users is an important step. But at present, given the variety of travel modes and business models, there is no clear indication of which mix of modes works best in each context. Much of the present literature is concerned with optimising single transport modes, without consideration for how different shared modes might be best integrated to meet the diverse needs of different populations.

This project will use a data-driven approach to develop national-level estimates of the locations where shared transport modes can best meet the mobility needs of places. As part of the INFUZE programme we will be bringing together data that characterise the mobility of places. Our partnerships on the project will enable access to data on shared transport mode use, business models, and population-scale mobility trajectories. These will be integrated additionally with contextual data relating to the urban environment – such as morphology, topography, land use / activity locations, and road network structure – and population data.

With data on potential demand and supply in place, this studentship will explore different ways to understand and measure the viability of different shared mode services, in combination, across different places. The specific approach will be developed during the first year, but could involve predicting usage patterns of alternative modes based on population and built environment factors, characterising places by their mobility (e.g. production of indices or segmentations of mobility behaviour), and/or optimising the mix of shared modes to meet different demands. An additional consideration relate to how we define place (i.e. what is a suitable spatial unit for planning these services) and how constraints are included, such as the space requirements of modes or likely fleet sizes (and subsequently their availability).

The outcomes of the studentship will potentially support local decision makers and service providers in better understanding how to different modes might combine to meet the mobility needs of a place.

Applicant skills/interests:

• Spatial / transport data science
• Machine learning
• Sustainable urban mobility
• Urban analytics

References

Golpayegani, F., Gueriau, M., Laharotte, P.A., Ghanadbashi, S., Guo, J., Geraghty, J. and Wang, S. 2022. Intelligent shared mobility systems: A survey on whole system design requirements, challenges and future direction. IEEE Access, 10, pp.35302-35320. DOI: https://doi.org/10.1109/ACCESS.2022.3162848

Jain, S., Ronald, N., Thompson, R. and Winter, S. 2017. Predicting susceptibility to use demand responsive transport using demographic and trip characteristics of the population. Travel Behaviour and Society, 6, pp.44-56. DOI: https://doi.org/10.1016/j.tbs.2016.06.001

Ma, X., Ji, Y., Yuan, Y., Van Oort, N., Jin, Y. and Hoogendoorn, S. 2020. A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data. Transportation Research Part A: Policy and Practice, 139, pp.148-173. DOI: https://doi.org/10.1016/j.tra.2020.06.022

Hua, M., Pereira, F.C., Jiang, Y., Chen, X. and Chen, J., 2024. Transfer learning for cross-modal demand prediction of bike-share and public transit. Journal of Intelligent Transportation Systems, pp.1-14. DOI: https://doi.org/10.1080/15472450.2024.2371913

Applicants should normally have at least an upper second class British Bachelors Honours degree (or equivalent) in geography or a related subject. A lower undergraduate degree can be supplemented by a relevant Masters degree. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the Postgraduate Research Admissions team prior to making an application.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.