Tree-Based Scenario Classification: A Formal Framework for Coverage Analysis on Test Drives of Autonomous Vehicles - Replication Artifact

Scenario-based testing is envisioned as a key approach for the safety assurance
of autonomous vehicles. In scenario-based testing, relevant (driving) scenarios
are the basis of tests. Many recent works focus on specification, variation,
generation and execution of individual scenarios. In this work, we address the
open challenges of classifying sets of scenarios and measuring coverage of
theses scenarios in recorded test drives. Technically, we define logic-based
classifiers that compute features of scenarios on complex data streams and
combine these classifiers into feature trees that describe sets of scenarios. We
demonstrate the expressiveness and effectiveness of our approach by defining a
scenario classifier for urban driving and evaluating it on data recorded from
simulations.

This artifact contains all files required to reproduce our experimental results.