Urban mobility in the age of AI
Project ID: 2531bd1628
(You will need this ID for your application)
Research Theme: Energy and Decarbonisation
Research Area(s):
artificial intelligence and data science
engineering for sustainability
infrastructure and urban systems
UCL Lead department: Centre for Advanced Spatial Analysis (CASA)
Lead Supervisor: Elsa Arcaute
Project Summary:
The project investigates how short-term urban mobility, particularly leisure trips, is being reshaped by the rise of large language models (LLMs) and digital recommender systems. It will explore how AI influences individual travel choices, how these choices feed back into collective patterns, and how such feedback loops transform urban environments. By studying the vulnerability of local businesses, the redistribution of urban “central places,” and the evolution of perceptions of neighbourhoods, the project aims to understand the role of digital systems in modelling mobility behaviour and shaping urban form.
Why the research is important
Digital platforms and AI tools increasingly influence everyday mobility decisions. This not only alters where people go, but also impacts local economies and reshapes urban hierarchies. Understanding these interactions is vital for anticipating risks, such as business vulnerability or urban inequality, and for designing more adaptive and resilient cities.
Who the student will be working with
The student will collaborate with the City Modelling Lab at ARUP, applying advanced tools and data from national multi-modal models, including synthetic population data derived from mobile phone records. The project will also link with a Horizon grant if funded, offering opportunities for international collaboration.
What the student will be doing
The student will design and run simulation and modelling experiments to capture the feedback between digital systems, mobility patterns, and urban change. They will analyse shocks to mobility, study visitation trends, and assess impacts on local businesses and urban structure using cutting-edge AI, data science, and network analysis methods.
Who UCL is looking for
We seek a motivated student with skills in data science, computer science, modelling, or urban analytics. Experience in coding, AI, or network science is desirable, alongside a strong interest in how digital technologies shape cities.