TY - CONF A1 - Khatun, Marzana A1 - Litagin, Heinrich A1 - Jung, Rolf A1 - Glaß, Michael A2 - Trapp, Mario A2 - Schoitsch, Erwin A2 - Guiochet, Jérémie A2 - Bitsch, Friedemann T1 - An Approach for Deriving Reduced Collision Scenarios for Highly Automated Driving Systems T2 - Computer Safety, Reliability, and Security. SAFECOMP 2022 Workshops: DECSoS, DepDevOps, SASSUR, SENSEI, USDAI, and WAISE Munich, Germany, September 6–9, 2022 Proceedings N2 - Scenario analysis is essential for the validation of highly automated driving (HAD) systems. The complexity of overall system safety is increasing in terms of Functional Safety (FuSa) and Safety of Intended Functionality (SOTIF). However, field testing of all possible safety-critical scenarios is hardly possible for automated vehicles. Therefore, scenario simulation is necessary for HAD to support the validation process and has gained acceptance in recent years. However, scenariobased analysis leads to an explosion of scenarios, so a scenario database is required at the beginning of the development phase. Hence, scenario reduction approaches need to be integrated in the conceptual phase to reduce the scenario modeling and testing effort. The contribution of this paper is to present simulation-based testing approaches for determining a reduced set of collision scenarios, taking into account the sensitivity of safety-critical parameters. Furthermore, a set of application scenarios is simulated to demonstrate the scenario reduction approaches by considering the detected collisions under a specific or restricted Operational Design Domain (ODD). In addition, this study supports the provision of a safety argument with evidence by introducing a variance-based sensitivity analysis and a scenario database that can be used as an input data set for an artificial intelligence system. KW - Highly Automated Driving System KW - CarMaker KW - Lane Change KW - Parameter variation KW - Functional Safety Y1 - 2022 UR - https://opus4.kobv.de/opus4-hs-kempten/frontdoor/index/index/docId/1404 SN - 978-3-031-14861-3 SN - 978-3-031-14862-0 SP - 166 EP - 177 PB - Springer Nature Switzerland CY - Cham ER -