## 1 Introduction  
In the past decade, as a result of the explosive growth in technology solutions, the automotive industry has undergone significant changes, resulting in the creation of highly automated functions meant to enhance traffic safety. However, the emerging systems pose serious challenges for professionals involved in vehicle testing and validation, as well as for the development of appropriate homologation procedures [1]. While previously, for more classical safety or assistance systems, test specifications consisted of a finite number of well-defined test cases, nowadays, for increasingly complex automation systems, the number of potential test cases has increased significantly. For example, in the past,testing an Electronic Stability Control (ESC) or Anti-lock Braking System (ABS) might have involved completing 10-15 test runs. Nowadays, defining test plans for certain Advanced Driver Assistance System (ADAS) functions could require over 50 or even more than 100 runs, especially in well-known assessment programs like European New Car Assessment Programme (EuroNCAP) active safety testing. The number of test runs required shows exponential growth. In the case of autonomous vehicles or Automated Driving Systems (ADS), an infinite number of traffic situations could easily generate thousands of relevant test scenarios in which the vehicle will have to perform adequately. For autonomous vehicles, there are not yet any universally accepted regulations; their development is still taking place intensively within various working groups, such as at the UN and the EU [2; 3]. Although there are various concepts for the appropriate selection of test cases, a unified procedure, especially with regard to the type approval of autonomous vehicles, has not yet been developed. Beyond type approval, other aspects such as liability, legislative issues or even interior designs, and necessary human-machine interfaces are not yet regulated or standardized [4]. One key milestone is the emergence of the New Assessment/Test Method for Automated Driving (NATM) document, which outlines a new test methodology for autonomous vehicles, relying on six main pillars, one of which is the possibility of generating a test scenario catalog [2]. The methodology is largely based on the methods established during the Pegasus project, according to which the concept of test scenarios has different contents and representations throughout the development process. The conceptual phase describes scenarios at a high level in natural language, while technical development and test scenario generation require representation with parameter spaces. The execution and evaluation of test scenarios require precisely defined cases in common data formats, which can be broken down into three levels of abstraction: functional, logical, and concrete [5]. Building on the work described in the above-mentioned studies, Regulation No. 171 was also developed, among others, which includes specific test cases for vehicles with higher levels of automation but allows for much greater flexibility in their exact definitions compared to the previous ADAS regulations, where both the manufacturer and the designated technical service such as Testing, Inspection, and Certification (TIC) companies play an important role. The regulation introduces requirements against Driver Control Assistance Systems (DCAS) including several basic test scenarios to which various more complex optional scenarios could also been defined [6]. These scenarios, among others, are also part of our utilized scenario database presented in the following sections. In the EU, Implementing Regulation 2022/1426 outlines guidelines and proposals for testing autonomous vehicles. When developing test scenarios, it is important to select cases that are adapted to the Operational Design Domain (ODD). An interesting point is that the regulation suggests incorporating existing test scenarios into the catalog (e.g., from EuroNCAP) if they are well suited to a particular circumstance.