CERTUS: An Automated AD/ADAS V&V Toolchain | Video Presentation by HORIBA MIRA

CERTUS: An Automated AD/ADAS V&V Toolchain | Video Presentation by HORIBA MIRA

CERTUS: An Automated AD/ADAS V&V Toolchain Video Presentation

This video presentation by Alejandro Trueba and Michael Orgill of HORIBA MIRA, introduces CERTUS, a toolchain designed for the verification and validation (V&V) of automated driving (AD) and advanced driver-assistance systems (ADAS). The toolchain aims to deliver efficient V&V through intelligent scenario generation, analysis, and reporting.

Key Points Covered:

Introduction to V&V Workflow:

  • Phases of V&V: Strategy, Scenario Definition, Test Planning, Test Execution, and Test Analysis.
  • Importance of defining, sampling, testing, assessing, analysing, and arguing scenarios.

Logical Scenario Example:

  • Differentiation between functional, logical, and concrete scenarios.
  • Example scenario: Car-to-Pedestrian Farside Adult 50%.

Orders of Magnitude:

  • Scope and coverage comparisons for different testing approaches (NCAP, Best Effort, Full Factorial).

Project Objective:

  • Efficient V&V through targeted scenario generation.
  • Addressing key questions: What to test, how to test, and when to stop.

CERTUS Features:

  • Analysis of Operational Design Domain (ODD) and deployment areas.
  • Use of metrics and oracles for performance risk quantification.
  • Search space optimization and scenario space sampling.

Battleship Analogy:

  • Illustration of problem space, stop criteria, feedback process, and decision-making in V&V.

Detailed Process:

  • Defining ODD, initial sampling, test generation, execution, and assessment.
  • Use of mixed reality tests and statistical methods for risk quantification.

Standards and Risk Quantification:

  • Reference to ISO 21448 SOTIF.
  • Importance of defining, modelling, and strategizing for residual risk assessment.

Core Innovations:

  • Intelligent scenario selection based on parameter sensitivity.
  • Mixed reality test environment.
  • Use of applied statistics for safety case justification.

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