| Qualification Type: | PhD |
|---|---|
| Location: | Norwich |
| Funding for: | UK Students |
| Funding amount: | £21,805 |
| Hours: | Full Time |
| Placed On: | 2nd November 2026 |
|---|---|
| Closes: | 24th February 2027 |
| Reference: | ZHANGU_U27SCI |
Primary Supervisor - Dr Xu Zhang
Urban mobility is undergoing rapid transformation through advances in autonomous aerial systems, electric vehicles (EVs), artificial intelligence, and connected transport technologies. While drones offer flexibility and rapid access to locations that may be difficult or inefficient to reach by road, ground vehicles provide greater carrying capacity, endurance, and access to established transport and energy infrastructure. Coordinating these complementary capabilities creates new opportunities for more efficient, sustainable, and responsive urban mobility systems.
This PhD project will investigate intelligent coordination between autonomous aerial systems and ground vehicles, particularly EVs, for future urban mobility applications. Rather than operating aerial and ground vehicles independently, the research will explore how they can cooperate in activities such as urban logistics, sensing, infrastructure monitoring, and other emerging city services. Key challenges include deciding how tasks should be allocated across heterogeneous vehicles, when and where vehicles should interact, and how routing, scheduling, charging and energy use can be jointly managed under dynamic urban conditions.
The project will develop optimisation and intelligent decision-making approaches for coordinating air–ground mobility systems in real time. Depending on the research direction, this may involve mathematical optimisation, scheduling algorithms, simulation, machine learning, or multi-agent decision-making. Particular attention will be given to dynamic demands, limited vehicle energy, heterogeneous operational capabilities, and the scalability of coordination across multiple vehicles.
Ultimately, the research aims to advance integrated air–ground mobility from independently operated vehicles towards intelligent, cooperative systems capable of supporting efficient and sustainable urban services.
Entry requirements
The standard minimum entry requirement is 2:1 in Mathematics, Computer Science, Electrical Engineering
Mode of study
Full-time
Start date
1 October 2027
Additional Funding Information
This PhD project is in a competition for a Faculty of Science funded studentship. Funding is available to UK applicants and comprises ‘home’ tuition fees and an annual stipend for 3 years. The current UEA / institutional PhD stipend rate is £21,805 and will be subject to any agreed inflationary uplift for 2027/28.
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