Developing the next generation of pedestrian behaviour models for revival of high streets and sustainable transport [Self-Funded Students Only]


   Cardiff School of Computer Science & Informatics

  Dr Crispin Cooper, Dr Christine Mumford  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Modelling the behaviour of pedestrians in city centres is of practical importance not only for sustainable transport (reducing reliance on motor vehicles addresses issues of carbon emissions, congestion and health) but also can help inform planning for town centres in a post-COVID world. High Street retail has long been in decline relative to out-of-town and online shopping; the pandemic has served to accelerate this process and the question of what a successful town centre will look like in 2030 remains open.

Our own previous research has included the first longitudinal strategic predictions of pedestrian flow [1], optimization of bus routes [2] and a classification of UK town centre types based on pedestrian sensor data [3].

The student would work on:

·      Methods for calibration of existing pedestrian simulations software such as www.cardiff.ac.uk/sdna to the diverse array of sensor, census and mobile phone data now available to determine which environments are more attractive for walking and when people will choose to walk

·      Methods for inclusion of more accurate built environment data into pedestrian models, e.g. by applying image recognition to freely available street view data

We have strong links with several transport consultancies and the Government High Streets Task Force to ensure models developed are both well aligned with the needs of city planners, and any results are likely to have real world impact.

Academic criteria: A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject.  Applicants with appropriate professional experience are also considered. Degree-level mathematics (or equivalent) is required for research in some project areas.

Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component.

How to apply:

Please contact the supervisors of the project prior to submitting your application to discuss and develop an individual research proposal that builds on the information provided in this advert. Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below

This project is accepting applications all year round, for self-funded candidates via https://www.cardiff.ac.uk/study/postgraduate/research/programmes/programme/computer-science-and-informatics 

In order to be considered candidates must submit the following information: 

  • Supporting statement 
  • CV 
  • In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal, as mentioned above in BOLD
  • Qualification certificates and Transcripts
  • Proof of Funding. For example, a letter of intent from your sponsor or confirmation of self-funded status (In the funding field of your application, insert Self-Funded)
  • References x 2 
  • Proof of English language (if applicable)

For more information about this project, please contact Dr Cooper,

If you have any questions or need more information, please contact 

Computer Science (8) Mathematics (25)

Funding Notes

This project is offered for self-funded students only, or those with their own sponsorship or scholarship award.

References

[1] C. H. V. Cooper, I. Harvey, S. Orford, and A. J. F. Chiaradia, ‘Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows’, Transportation, Dec. 2019, doi: 10.1007/s11116-019-10072-0.
[2] L. Ahmed, P. Heyken-Soares, C. Mumford, and Y. Mao, ‘Optimising bus routes with fixed terminal nodes: comparing hyper-heuristics with NSGAII on realistic transportation networks’, in Proceedings of the Genetic and Evolutionary Computation Conference, New York, NY, USA, Jul. 2019, pp. 1102–1110, doi: 10.1145/3321707.3321867.
[3] C. Mumford, C. Parker, N. Ntounis, and E. Dargan, ‘Footfall signatures and volumes: Towards a classification of UK centres’, Environment and Planning B: Urban Analytics and City Science, p. 2399808320911412, Mar. 2020, doi: 10.1177/2399808320911412.

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