Simulation-Based Logical Scenario Generation and Analysis Methodology for Evaluation of Autonomous Driving Systems

The safety of autonomous driving systems (ADSs) must be assessed through different scenarios before ADSs can be deployed. Scenario representation is a method to condense the infinite number of scenarios that can occur in real-world traffic into a finite set to facilitate testing. The scenarios are categorized into four levels: functional, abstract, logical, and concrete. A logical scenario is one in which the parameters representing the scenario are defined in the form of ranges. Research has been conducted on real-world traffic to derive reasonable ranges for logical scenario parameters. However, such studies incur elevated costs for scenario detection, lack consideration of hazardous situations, and suffer from driving style–related and regional biases in data. Therefore, this study introduces a simulation software–based method to overcome the cost and data bias problems while generating logical scenarios that account for both normal and hazardous situations. The proposed method involves analyzing the results for three of the scenarios specified in the ISO 34502 standard and qualitatively validating the findings against results from studies using real-world vehicle data.