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Parking demand modelling and availability forecasting

Study level

PhD

Master of Philosophy

Faculty/Lead unit

Science and Engineering Faculty

School of Civil Engineering and Built Environment

Topic status

We're looking for students to study this topic.

Supervisors

Dr Behrang Assemi
Position
Postdoctoral Research Fellow
Division / Faculty
Science and Engineering Faculty
Professor Douglas Baker
Position
Professor
Division / Faculty
Science and Engineering Faculty

Overview

Patterns of on-street parking utilisation are yet under-explored and there is a need to develop a deeper understanding of the users, their needs and their behaviours; especially given that land-use and population density has continued to change in our cities.

Moreover, new business delivery models have emerged, such as ridesharing and electric vehicles. The coming introduction of disruptive technologies, such as smart objects, machine learning, autonomous and semi-autonomous vehicles, will add an additional requirement to rapidly respond to customer needs.

This project aims to conduct an in-depth analysis of parking behaviour, customer needs and potential changes in the future and to develop strategies for more sustainable parking planning and management in high-density urban areas.

Research activities

You will meet regularly with your supervisors to acquire new knowledge, brainstorm ideas, discuss your progress and receive direction on future work.

This project will involve:

  • conducting surveys
  • data manipulation and analysis
  • statistical analysis (especially time series analysis and cluster analysis)
  • communicating your work in written and oral forms.

Outcomes

You will develop new skills in:

  • statistical modelling
  • time series analysis
  • reproducible research
  • literate programming.

If you are a masters or a PhD student, you will be expected to present your work at international conferences. You will then have your findings published in scientific journals.

Skills and experience

This project can be personalised to suit your individual interests and skills and can be tailored to your masters or PhD studies. We will assume that you have some proficiency in R/Python, multivariate statistical analysis and statistical model development.

Scholarships

You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round

Keywords

Contact

Contact the supervisor for more information.