Autonomous systems are becoming used more and more in various industrial and other application domains, e.g. in automotive applications and transportation, surveillance, rescue, construction industry, or in home-care. These systems take over activities traditionally performed by humans, are often safety critical and need to be highly reliable, available and maintainable. Therefore, the dependability and risk control becomes crucial, requiring new paradigms and methodologies for software development as well as for system validation through appropriate analysis and tests.  

Our ambition at AIT is to make autonomous and complex systems highly reliable and safe. Research within the Safety and Security Department puts particular emphasis on the automotive sector. We develop methods and tools used to design in-vehicle communication networks and to simulate the entire data flow and effect chain for standard bus systems e.g. LIN, CAN and FlexRay. 

Testing of safety-critical systems amounts to up to 70 per cent of their total development costs. A key issue here is the selection of test cases, with respect to both coverage (completeness) and efficiency. For simple applications with a few input parameters, exhaustive combination of input values may yield the required coverage across an acceptable amount of test cases. For autonomous systems with complex behaviour and high-dimensional sensors such as cameras, however, this approach is unsuitable. Our focus, therefore, lies on model-based test-case generation. We exploit the benefits of formal methods and use tools and automation in order to make testing of real-world systems more meaningful, while drastically reducing the associated costs. The development and effort of model-based (security)analysis methods depict another ambition for an early recognition of potential design errors.

We offer contract research and innovations in the following fields of expertise:

• Methods and tools
• Certification, analysis, and design
• Operational oversight and active participation