A Review of Scenario Similarity Measures for Validation of Highly Automated Driving

Automated driving systems have the potential to change our transportation in the future. Since they represent safety-critical systems in an open-world context, achieving a sufficient level of safety and acceptance is a significant concern. Research and industry focus on scenario-based testing to handle the increasing verification and validation activities. A scenario catalog builds the foundation for the test cases to achieve sufficient test coverage. Although they are often not formally defined, scenario similarities and distances are commonly and implicitly used to describe and measure relationships between scenarios during testing. This paper provides an overview of existing measures used for comparing scenarios based on the dynamic behavior of their traffic participants, and how these measures are applied in testing. Therefore, a formal definition of scenario distance, similarity measures, and processable scenario types is introduced. Possible applications are identified and allocated to the scenario-based testing process. It is highlighted how the presented structured understanding of this topic helps to transfer and reuse an existing similarity or distance measure for multiple applications and to create meaningful combinations of those measures to consider all aspects of scenarios comprehensively. This facilitates a more consistent and efficient validation process.