Wir entwickeln innovative Sicherheitskonzepte und bringen einen digitalen »Safety-Ingenieur« an Board, der das automatisierte Fahren sicherer macht.
Chip design verification is dominated by manual interpretation of complex DRAM standards. With DRAMPyML and DRAMBench, Fraunhofer IESE and Normal Computing introduce timed Petri net models and an open benchmark to autoformalize memory specifications. This post shows how AI can…
Hardware bottlenecks are the invisible anchors dragging down modern automotive development. As Software Defined Vehicles (SDVs) grow in complexity, development teams often find themselves stalled, waiting for access to physical test rigs like the NXP GoldBox. At Fraunhofer IESE, we…
Ensuring safety in Autonomous Driving Systems (ADS) as they transition between different Operational Design Domains (ODDs) is both challenging and crucial. In our research projects, we found that there are no established methods out there for modeling, analyzing, and documenting…
Unlocking Automotive Safety: How LLM-Augmented Tools Are Transforming Hazard and Risk Assessments In the ever-evolving landscape of automotive safety engineering, the Hazard Analysis and Risk Assessment (HARA) process is crucial. This procedure demands extensive engineering expertise to meet the requirements…
Im Wettbewerb um Technologien und Zukunftsmärkte spielen Normen und Standards eine entscheidende Rolle. Das Positionspapier »Wer sie gestaltet, beherrscht den Markt: Normen und Standards« der Fraunhofer-Gesellschaft weist darauf hin, wie wichtig die Gestaltung von Normung und Standardisierung ist und formuliert…
The use of Machine Learning (ML) components in safety-critical or financially critical systems is challenging. At Fraunhofer IESE, we address this challenge by systematically engineering comprehensive multi-layered safety concepts and explicitly considering sources of uncertainties. This specifically includes situations at…
The evolution of vehicle infotainment systems has dramatically enhanced the driving experience. This is achieved by incorporating advanced functionalities such as navigation, multimedia, and connectivity options. Therefore, meticulous testing is crucial to ensure the reliability and functionality of these sophisticated…
Development and testing of Advanced Driver Assistance Systems (ADAS) and autonomous driving technologies are of paramount importance in the rapidly evolving automotive industry [1]. Therefore, in collaboration with our industrial partners aSR and CADFEM, we built a driving simulator that…
Introduction Creating and configuring simulation scenarios is effort-intensive and time-consuming, mainly because each scenario requires a unique set of configurations, parameters, and settings, making the procedure time-consuming and error-prone. This complexity not only reduces productivity but also increases the learning…
Das autonome Fahren, insbesondere abseits von Straßen, ist aufgrund der Umgebungsvielfalt und Unvorhersehbarkeit unterschiedlicher Situationen fehleranfällig. Ein Lösungsansatz für dieses Problem ist es, durch das Imitieren menschlicher Denkmuster die Leistung von Künstlicher Intelligenz (KI) zu steigern, um ein Kontextbewusstsein in…
