Cooperative Perception, World Modelling, and Intelligent Control for Autonomous Vehicle Systems
Not stated
- Location
- Birmingham, United Kingdom
- Funding
- See advert
- Application deadline
- Year-round applications
About the project
About the Project About the Project This PhD project focuses on the development of next-generation autonomous technologies that combine vehicle control with advanced environmental perception. You will explore how real-time sensing, multi-sensor fusion, world modelling, spatial intelligence, and intelligent algorithms can jointly enable safer, greener, and smarter vehicle operations or asset management. Key research topics include environment cooperative perception, multi-sensor calibration, visual localisation, and AI-based vehicle control. By leveraging onboard and infrastructure-supported sensors (such as camera, radar, and LiDAR), your work will enhance a vehicle’s ability to perceive its environment and respond optimally in dynamic operating conditions. A particular research direction may involve the development of world models capable of learning the spatial dynamics of transport environments, including the prediction of future states and behaviours of vehicles, pedestrians, and other objects. These models could support scene understanding, decision-making, and trajectory planning in complex and previously unseen situations. You may also explore multimodal foundation models, vision-language models, or other emerging AI approaches for combining visual and contextual information to improve perception and autonomous decision-making. Meanwhile, you will also develop intelligent control strategies that minimise energy use while ensuring punctuality, operational efficiency, and safety. Alternatively, you could investigate how perception and vision-based localisation systems can support accurate vehicle positioning, particularly in GNSS-denied environments (e.g. tunnels). By using perception technologies, the research could enable reliable localisation where satellite-based positioning is unavailable, supporting safer autonomous operation and navigation. Core research themes include: Cooperative perception and infrastructure-assisted sensing Multi-sensor calibration and real-time sensor fusion World models, dynamic scene understanding and future-state prediction Visual localisation, spatial intelligence and environment mapping Eco-driving and optimal control for energy-efficient vehicle operation AI-driven modelling and intelligent control in transport environments Autonomous vehicle decision-making and trajectory planning Our group already has perception system developed and a large amount of first-hand, self-collected multimodal datasets available for use. You will work closely with industrial partners, gaining access to experimental platforms, real-world data, and test environments.