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- Safeguarding of artificial intelligence (AI)
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Safety verification according to SOTIF - How safe is safe enough?
The verification of functions for highly automated driving is the central focus of all manufacturers and suppliers. The effort involved for the proof of safety is enormous. Current concepts require hundreds of thousands of scenarios and hundreds of millions of test kilometres.
The ISO/DIS 21448 standard addresses the safety of intended functionality (SOTIF) for advanced driver assistance systems (ADAS) and autonomous vehicle functions. The emerging standard on safety of intended functionality SOTIF (ISO / DIS 21448) complements the current standards and addresses additional safety risks that only arise due to the complexity of the application environment.
Current verification methods - virtual or real - are severely limited in terms of completeness, representativeness, reproducibility and especially in borderline situations. In addition, current standards, e.g. ISO 26262 on functional safety for safety-critical E/E systems and ISO/SAE 21434 on cyber security, do not fully cover the industry's requirements for safeguarding highly automated driving functions.
The safeHAD method: Managing the safety case according to SOTIF
The IABG method safeHAD makes the SOTIF standard applicable in practice and provides reliable statements for proving the safety of highly automated driving functions - customer-specific and efficient.
With safeHAD, we have developed a method that makes the SOTIF standard usable in your development process. We support you both holistically and selectively in the management of the safety verification according to SOTIF for your functionality:
- SOTIF process consulting
- Development of the SOTIF argumentation structure in Goal-Structuring-Notation
- Analysis and integration of existing artefacts
- Methodology safeHAD incl. software tool
- Coverage and V&V strategy
- Risk assessment and proof of SOTIF arguments (evidence)
safeHAD is a tool-supported procedure for the systematic evaluation of the specified test space (ODD) of the investigated driving function. Here, virtual and real test results are evaluated combinatorially in a Python framework.
The conformity to the widespread ASAM standards and conventions such as OSI, OpenSCENARIO, OpenDRIVE, OpenODD and OpenLabel enables an easy coupling and extension of your toolchain.
In addition to quantifying the remaining residual risk (area 2 unsafe unknown) for the target function, safeHAD determines the occurrence probabilities of accidents of various severity levels - from rough estimates in the concept phase to precise estimates in the release procedure.
In early phases, design alternatives can thus be compared, analysed and evaluated in order to identify system weaknesses in good time and avoid wrong decisions. In the later phases of product development, safeHAD provides a robust safety assessment for function release and system approval (SOTIF release).
safeHAD makes your systems testable according to the SOTIF standard ISO 21448 and thus enables a resilient proof of safety within the scope of type approval.
We advise you, guide you through the process and take over the application of the methodology - tailored to your function and your system components.
How you benefit from safeHAD
- Save time and money,
by using safeHAD to identify weak points in good time and avoid costly troubleshooting at a later stage.
- Improve the quality of your products and your competitiveness,
by deriving and verifying well-founded requirements for the function and system components at an early stage.
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