Modern transportation is undergoing a profound transformation driven by electrification, automation, connectivity, and artificial intelligence. From road vehicles and rail systems to emerging mobility platforms and autonomous transport technologies, there is a growing need for intelligent control systems capable of operating safely and effectively in complex and uncertain environments.
A key challenge across many transportation domains is maintaining stability, safety, and optimal performance while responding to changing operating conditions, environmental disturbances, and evolving system demands. Advances in sensing, computation, machine learning, and distributed actuation are creating exciting opportunities to develop more adaptive, intelligent, and responsive control strategies capable of supporting future mobility systems.
This research will investigate advanced approaches to stability, control, and autonomous decision-making within intelligent transportation systems. The project will explore how modern control theory, artificial intelligence, machine learning, optimisation, and data-driven modelling techniques can be integrated to improve system performance, robustness, efficiency, and operational safety.
Depending on the candidate's interests and project direction, applications may include intelligent road vehicles, electric and autonomous transportation systems, rail transport, connected mobility platforms, smart infrastructure, robotic transportation technologies, and other emerging transport solutions.
The research will involve the development of mathematical models, simulation environments, and intelligent control frameworks to analyse and optimise the behaviour of complex transportation systems under realistic operating conditions.
As a PhD candidate, you will:
- Develop expertise in intelligent control systems, autonomous decision-making, and transportation technologies.
- Investigate advanced modelling, optimisation, and machine learning approaches for dynamic systems.
- Explore novel methods for improving stability, safety, efficiency, and resilience in transportation applications.
- Design and evaluate intelligent algorithms using state-of-the-art simulation and computational tools.
- Work at the intersection of artificial intelligence, control engineering, transportation systems, and automation.
- Contribute to research that supports the future of sustainable, connected, and autonomous mobility.
This interdisciplinary project combines elements of control engineering, artificial intelligence, robotics, transportation systems, and digital technologies, providing an excellent opportunity to work on challenges that are shaping the future of mobility worldwide.
We are seeking highly motivated candidates with strong analytical and problem-solving skills and a background in engineering, computer science, mathematics, physics, or related disciplines. Experience in areas such as control systems, machine learning, optimisation, robotics, simulation, programming, data science, or intelligent systems would be beneficial but is not essential.
