Reducing the Number of Scenarios in Automated Driving Systems: Methods and Strategies

This study focuses on reducing the number of scenarios in scenario-based testing processes for AD systems. Due to the complexity of AD systems, traditional distance-based testing methods prove insufficient, making scenario-based testing a more efficient solution. The study examines methods such as parameter elimination, boundary narrowing, and optimization/searching to reduce and optimize the number of test scenarios. These approaches aim to streamline testing by reducing costs and time while ensuring the safety validation of AD systems. Through the proposed strategies, non-critical scenarios can be filtered out, and critical scenarios can be prioritized for testing