Tackling Uncertainty in AI for Safer Autonomous Systems
Within the SAFEXPLAIN project, members of the Research Institues of Sweden (RISE) team have been evaluating and implementing components and architectures for making AI dependable when utilised within safety-critical autonomous systems. To contribute to dependability...
SAFEXPLAIN shares its safety critical solutions with aerospace industry representatives
On 12 May 2025, the SAFEXPLAIN consortium presented its latest results to representatives of several aerospace and embedded system industries including Airbus DS; BrainChip, the European Space Agency (ESA), Gaisler, and Klepsydra, showcasing major strides in making AI...
SAFEXPLAIN Update: Building Trustworthy AI for Safer Roads
For enhanced safety in AI-based systems in the railway domain, the SAFEXPLAIN project has been working to integrate cutting-edge simulation technologies with robust communication frameworks. Learn more about how we’re integrating Unreal Engine (UE) 5 with Robot Operating System 2 (ROS 2) to generate dynamic, interactive simulations that accurately replicate real-world railway scenarios.
Enhancing Railway Safety: Implementing Closed-Loop Validation with Unreal Engine 5 and ROS 2 Integration
For enhanced safety in AI-based systems in the railway domain, the SAFEXPLAIN project has been working to integrate cutting-edge simulation technologies with robust communication frameworks. Learn more about how we’re integrating Unreal Engine (UE) 5 with Robot Operating System 2 (ROS 2) to generate dynamic, interactive simulations that accurately replicate real-world railway scenarios.
Case Studies Update: Integrating XAI, Safety Patterns and Platform Development
The SAFEXPLAIN project has reached an exciting point in its lifetime: the integration of the outcomes of the different partners.
The work related to the case studies began with the preparation of AI algorithms, as well as the datasets required for the trainings and for the simulation of the operational scenarios. Simultaneously, the case studies have counted on support from the partners focused on explainable AI (XAI), safety patterns and platform development.
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