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| en:safeav:curriculum:avt-m [2025/11/05 07:20] – raivo.sell | en:safeav:curriculum:avt-m [2025/11/05 09:21] (current) – airi | ||
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| ^ **Study forms** | Hybrid or fully online | | ^ **Study forms** | Hybrid or fully online | | ||
| ^ **Module aims** | The aim of the course is to introduce the principles, methods and tools used for verification and validation of autonomous and other safety-critical cyber-physical systems. The course develops students’ ability to design, implement and critically assess physical, virtual and hybrid validation workflows in line with relevant industrial practices and standards, preparing them to apply these approaches in advanced engineering projects and research. | ^ **Module aims** | The aim of the course is to introduce the principles, methods and tools used for verification and validation of autonomous and other safety-critical cyber-physical systems. The course develops students’ ability to design, implement and critically assess physical, virtual and hybrid validation workflows in line with relevant industrial practices and standards, preparing them to apply these approaches in advanced engineering projects and research. | ||
| - | ^ **Pre-requirements** | Solid background in control engineering, | + | ^ **Pre-requirements** | Solid background in control engineering, |
| ^ **Learning outcomes** | **Knowledge**\\ • Explain the role and structure of verification and validation in the autonomy lifecycle.\\ • Describe international standards and their influence on testing processes.\\ • Understand the architecture of physical, virtual, and hybrid test environments for autonomous systems.\\ • Identify limitations and emerging research trends in simulation-based validation and safety case generation.\\ **Skills**\\ • Design and execute test plans using real and simulated environments.\\ • Apply AI-driven methods for scenario generation, coverage analysis, and failure detection.\\ • Integrate scenario building toolchains into validation workflows.\\ • Assess compliance and produce documentation aligned with certification processes.\\ **Understanding**\\ • Appreciate the interdependence of testing, regulation, and ethical assurance in autonomous systems.\\ • Recognize challenges of validating stochastic, learning-based algorithms.\\ • Demonstrate accountability, | ^ **Learning outcomes** | **Knowledge**\\ • Explain the role and structure of verification and validation in the autonomy lifecycle.\\ • Describe international standards and their influence on testing processes.\\ • Understand the architecture of physical, virtual, and hybrid test environments for autonomous systems.\\ • Identify limitations and emerging research trends in simulation-based validation and safety case generation.\\ **Skills**\\ • Design and execute test plans using real and simulated environments.\\ • Apply AI-driven methods for scenario generation, coverage analysis, and failure detection.\\ • Integrate scenario building toolchains into validation workflows.\\ • Assess compliance and produce documentation aligned with certification processes.\\ **Understanding**\\ • Appreciate the interdependence of testing, regulation, and ethical assurance in autonomous systems.\\ • Recognize challenges of validating stochastic, learning-based algorithms.\\ • Demonstrate accountability, | ||
| ^ **Topics** | 1. Overview of Verification and Validation: | ^ **Topics** | 1. Overview of Verification and Validation: | ||
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| ^ **Recommended tools and environments** | MATLAB/ | ^ **Recommended tools and environments** | MATLAB/ | ||
| ^ **Verification and Validation focus** | | | ^ **Verification and Validation focus** | | | ||
| - | ^ **Relevant standards and regulatory frameworks** | ISO 26262, ISO 21448 (SOTIF), DO-178C, UL 4600, IEEE P2851 | | + | ^ **Relevant standards and regulatory frameworks** | ISO 26262, ISO 21448, DO-178C, UL 4600, IEEE P2851 | |
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