Test Case Derivation for Automated Vehicles Based on Relevance and Test Method Rating of Possible Scenarios

Authors

Dr.-Ing. Andreas Pütz, Ford-Werke GmbH, Aachen, Germany;
Sari Kassar, M.Sc. Ford Motor Company, Dearborn, USA;
Lennart Vater, M.Sc., Univ.-Prof. Dr.-Ing. Lutz Eckstein, Institute for Automotive Engineering (ika), RWTH Aachen University, Aachen, Germany

Summary

Due to the anticipated high mileage required for the safety approval of automated vehicles by pure mileage accumulation, the scenario-based testing currently becomes more and more established for the verification and validation of these systems. Within the Pegasus project, a methodical framework on how to derive test cases based on input data for various driving data sources was proposed. The present paper adopts this approach, applies it on a currently developed feature and enhances it by suggesting an automatic relevance and test method rating for scenarios that automated vehicles might face during its operation. This increases the efficiency of the testing procedure by allowing test case prioritization based on objective and traceable criteria.

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