Course paper / final thesis

Air Traffic Controller Command Prediction based on a state machine

Starting date


Duration of contract

6 months

Type of employment


"Cutting-edge research requires excellent minds – particularly more females – at all levels. Launch your mission with us and send in your application now!" Prof. Pascale Ehrenfreund - Chair of the DLR Executive Board

The department controller assistance develops prototypic support systems for air traffic controllers. Controllers issue commands to aircraft pilots via voice. These commands also need to be entered into the air traffic control system to enable support functionalities for controllers. Entering such commands via keyboard or mouse creates additional effort for controllers. Furthermore, the relevant information already exists within the verbal command. Hence, automatic speech recognition is used to extract the contents of controller commands to feed the air traffic control system.

DLR developed an assistant based speech recognition (ABSR) system with command recognition error rates below 1 % for the approach area. The ABSR consists of a speech recognition engine and a command hypotheses generator forecasting the most probable commands in the current situation. These commands reduce the search space for the speech recognizer and lead to lower command recognition error rates. In a first version, hypotheses were rely on radar data, flight plan data and meteorological data as well as expert knowledge about the airspace and air traffic in a specific environment. An enhanced version of the hypotheses generator used machine learning algorithms to forecast commands for all relevant aircraft depending on their position. For the first time, hypotheses have also been generated for the tower area automatically learned from annotated speech and radar data.  For even more accurate forecasts, a state machine approach should be used. Particularly aircraft on the ground follow a sequence of actions respectively states such as engine start-up, pushback, taxi, line-up, and take-off, etc. If it is known, which commands the aircraft has already received respectively executed, the number of predicted commands can be further reduced. This knowledge can be generated from radar as well as speech data with some lower accuracy (probability) from the speech recognition system itself. Hence, algorithms should be developed to forecast controller commands based on a state machine approach assigned with a probability. Those hypotheses should then be evaluated against recorded data from human-in-the-loop trials with tower controllers from Hungary and Lithuania.
In the course of your master’s/bachelor’s thesis, the following tasks need to be handled:

  • Familiarisation with the concepts of assistant based speech recognition and command hypotheses in air traffic control
  • Development of concept for a state machine based on available data to predict future controller commands with probabilities (focus on tower commands)
  • Implementation of algorithms and tests into existing source code of our controller support toolbox
  • Continuous documentation of working steps and results

Your qualifications:

  • Studies in Informatics, Computer Science, Aviation or similar
  • Good programming skills (e.g., C++)
  • Good knowledge in writing scientific essays (e.g. seminar thesis)
  • Background knowledge about air traffic control completes your profile in the best case

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

  • Apply online now
  • You can send this job advertisement via e-mail and complete your application on a personal computer or laptop.

    We need your digital application documents (PDF). The document upload function is not supported by all mobile devices. Please complete your application on a PC/laptop.

    Complete application on PC

Technical contact

Dr Oliver Ohneiser
Institute of Flight Guidance

Phone: +49 531 295-2566

Send message

Vacancy 47279

HR department Braunschweig

Send message

DLR site Braunschweig

To location

DLR Institute of Flight Guidance

To institute