Background

Air Traffic Management (ATM) and Communications, Navigation, and Surveillance (CNS) systems form the operational foundation of civil aviation. Current operations depend heavily on centralized ground facilities and satellite services for surveillance and management. This system is vulnerable for a range of disruptions including infrastructure failures, GNSS outages or cyber incidents. These vulnerabilities can degrade or even halt civil aviation.

Project ORION (Onboard Resilient Infrastructure-free Operational Network) investigates an alternative ATM/CNS architecture designed to function without reliance on ground- or space-based infrastructure. By utilizing an aeronautical ad-hoc network for communication, relative positioning, and surveillance, ORION aims to enable aircraft to self-organize and maintain safe separation thus ensuring a minimum service level even during (large scale) disruptions.

Project description

This PhD project is fundamentally multidisciplinary. As a PhD candidate, you will design, model, and evaluate a decentralized ATM/CNS architecture. The research focuses on determining how core traffic management functions can be sustained through cooperation using an aeronautical network when centralized ground and satellite services are unavailable.

In the first phase of the research, you will determine a set of use cases and design the underlying aeronautical ad-hoc networking concept layer to enable direct airborne data exchange, cooperative relative localization, and cooperative surveillance.

Next, building on this network layer, you will formulate distributed algorithms for fundamental traffic management functions, including aircraft-as-a-sensor (mesh network), separation assurance, conflict detection and resolution, and traffic sequencing.

Finally, to evaluate the operational feasibility of the architecture, you will implement the models within an ATM simulation platform, such as the open-source simulator BlueSky. For this you will extend the platform to include the ad-hoc networking functionality. Using this environment, you will stress-test the system under severe disruption scenarios by comparing the overall performance directly against conventional centralized ATM/CNS operations. This will provide evidence of the performance of the models for the various use-cases.

Your profile

• Master’s degree in Aerospace Engineering, Computer Science, Applied Mathematics, or a related field;

• Strong analytical and mathematical foundation, with experience in or a keen aptitude for complex systems modelling and distributed systems;

• Multidisciplinary mindset with the ability to bridge distinct domains: connecting operational ATM concepts with distributed network protocols and algorithm design;

• Strong background in programming, using Python or other relevant programming languages;

• Good scientific reporting and communication skills in written and spoken English.

What we offer you

You will receive a 4-year research contract from NLR and will join the Air Traffic department. In addition, you will be enrolled in the Doctoral Education programme of the Graduate School at Delft University of Technology (TU Delft). During this period, you will work closely with NLR colleagues in Amsterdam and with academic supervisors from TU Delft. Your working week will ideally be divided into: 2 days in Amsterdam, 2 days in Delft, and 1 day from home.

In addition, we offer:

• No fewer than 45 days off (with full-time employment);

• A fixed end-of-year bonus of 8%;

• A contribution towards your healthcare costs;

• Extra paid parental leave;

• The possibility to work from home where possible.

Would you like to know more?

Please visit https://www.tudelft.nl/en/ae/research/ae-graduate-school for more information on the graduate school.

For more information about the recruitment procedure, contact Pien Moller (recruiter) via [email protected].

Would you like to apply?

Great, we are curious about you! Send your motivation letter and CV via the apply button!

A pre-employment security screening (VGB-C) is a requirement. For more information about the screening, please visit the AIVD website.

Acquisition in response to this vacancy is not appreciated.