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PhD student: Detect and Avoid for Extreme Traffic Densities

Research / Academic
Delft

Description:

Unmanned flying vehicles, or drones, are increasingly being seen as a suitable platform for a wide range of applications, from inspecting infrastructure and aerial photography, to parcel delivery, search and rescue, and many other applications. Unlike current-day manned aviation, many of these envisioned drone applications would involve operation in heavily-constrained urban airspace, and when successful, at extreme traffic densities, compared to current operations.

Currently, several large research efforts are formalizing the procedures and services that will be required for these operations (e.g., U-Space in Europe, UTM in the US). A critical, but currently underexposed aspect in these concepts of operations is the development of a robust Detect and Avoid (D&A) system that is able to function at extreme traffic densities, for a wide mix of different vehicle types. As the extreme densities rule out a fully centralized system, decentralized D&A will be required, and coordination between vehicles (implicit or explicit) will be imperative. Previous research has shown that this becomes increasingly problematic once more than two vehicles are involved. As part of your PhD research, you will therefore design and test decentralized resolution algorithms to solve this problem. Methods you will investigate include, among others, global optimization methods adapted to local resolution, and reinforcement learning techniques, as well as various levels of intent communication. You will publish your results in leading, peer-reviewed journals. These publications will be combined in your final dissertation.

As part of your PhD, you will also work in an international (EU-funded) consortium, on airworthiness standards for drones in Europe. Supported by the renowned MAV laboratory of TU Delft this will give you the opportunity to cooperate with major players in drone research and industry and build an extensive network already during your PhD.

Requirements:

The PhD position is funded by the H2020 AW-DRONES project. You will be working in an international consortium, which means that good proficiency in the English language (spoken and written) is required. Furthermore, the position requires an MSc in Aerospace Engineering, Aeronautics or a comparable degree, thorough knowledge of air traffic management, flight operations, as well as excellent programming (C++, Python, …) and mathematical skills. Preferably you also already have experience in writing scientific reports and papers.

Salary Benefits:

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information.

For more information about this vacancy, please contact Joost Ellerbroek, Assistant Professor, phone: +31 (0)15-2789613, e-mail: J.Ellerbroek@tudelft.nl. For more information about the selection procedure, please contact Bertine Markus, Secretary, e-mail: B.M.Markus@tudelft.nl.

To apply, please e-mail a detailed CV along with a letter of application to Joost Ellerbroek, e-mail: J.Ellerbroek@tudelft.nl.
When applying for this position, please refer to vacancy number LR18.26.

Work Hours:

38 hours per week

Address:

Kluyverweg 1