Artificial Intelligence European certification under Industry 4.0


fortiss is contributing to approaches designed to enable the certification of symbiotic human-machine systems in the “cockpit and training assistance system” application scenario and to develop formal verification concepts for validating the resiliency of AI onboard applications.

Project description

The capacity of the civilian air traffic system has been stretched to its limits for years, leading to increased delays and flight cancellations. Overcoming these capacity bottlenecks requires a wide of range of efforts. From a technical standpoint, artificial intelligence (AI) could play a key role, such as by enabling more effective air space monitoring or single-pilot operation in cases where regulations require at least two pilots. The issue is that the non-transparency and complexity of many AI systems represents a major challenge for the safe deployment of this technology in the aviation sector. As part of the joint project KIEZ4-0 (A German acronym meaning certified artificial intelligence in the European airspace under Industry 4.0), fortiss is researching concepts with the project partners to determine how the reliability of AI-supported aviation applications, such as single-pilot operation, can be certified. Using a flight mission management application, the project team is also examining what type of formal methods could contribute to the certification of such systems.

Research contribution

Concepts and guidelines for designing human-machine interaction for the certification of AI applications.

  • Human factors validation methods to ensure the seamless interaction and trustworthy relationship between humans and machines.
  • Formal verification methods as a building block for the safety assurance of AI-based systems.
  • The developed methods and guidelines can impact the certification of AI and serve as the foundation for national and international regulation.
  • The results will be integrated into national and international committees in order to advance harmonization and standardization.
  • Adaptation of the results to other domains by transferring the developed methods and establishing them in areas such as robotics, manufacturing or autonomous driving.

Project duration

01.07.2020 – 31.12.2023

Dr. Yuanting Liu

Your contact

Dr. Yuanting Liu

+49 89 3603522 427

Project partner