Understanding the Human Spatial Navigation in Complex Urban Environment

About the Project

This research project is centred on the study of human navigation in urban environments, leveraging the latest advancements in VR, robotics, computer vision, and AI technologies.

Project Overview: This PhD studentship focuses on developing an in-depth understanding of how humans perceive, interact with, and navigate complex urban environments. The research will leverage state-of-the-art technologies, including mobile eye-tracking, Virtual Reality (VR), Simultaneous Localisation and Mapping (SLAM), motion tracking, and deep-learning-based computer vision, to capture and analyse the dynamics of human movement and spatial awareness across a range of urban navigation scenarios.

The project aims to characterise human–environment interactions at behavioural, computational, and sensorimotor levels, with particular emphasis on visual attention, spatial cognition, and movement strategies in realistic urban settings. By integrating immersive VR experiments with real-world sensing and AI-driven analysis, the research will provide high-resolution, ecologically valid insights into human navigation behaviour.

The studentship will be closely supported by industry partners, including Meta, with whom the host laboratory maintains an active research partnership. These collaborations will provide access to advanced hardware platforms, data-collection technologies, and translational perspectives, strengthening the project’s methodological and applied impact.

Outcomes from this research are expected to have significant implications for urban planning and design, transportation safety, autonomous and human-centred vehicle systems, and neuroscience, contributing to a deeper and more quantitative understanding of human–environment interactions in urban contexts.

List of other projects related/available in the lab can be found here: https://sites.google.com/view/yeolabprojects

Candidate Requirements: The ideal candidate will possess a strong academic background in psychology, geography, engineering, computer science, applied mathematics, or a related field with a first-class honour (70% and above). As the project requires intensive use of state-of-the-art techniques, prior coding experience in deep-learning computer vision algorithms or ROS would be preferred. More importantly, essential to this role is the ability to independently conduct research activities. We seek a researcher with a keen interest in technology and innovation, capable of handling complex datasets and eager to explore the intersection of human behaviour and technology in outdoor environments.

University Environment and Support: The candidate will become part of a vibrant academic community of The Unversity of Birmingham, gaining access to a range of resources and facilities. The host department, The School of Sport, Exercise and Rehabilitation Sciences, is committed to providing a supportive environment for professional development, including opportunities for presenting research findings at international conferences and publishing in respected journals.

This is a project for self-funded students only. Interested applicants with any questions regarding the project, please contact Dr Yeo (s.yeo@bham.ac.uk).