Methodology for Test Case Allocation based on a Formalized ODD

2025-09-02

AI Summary

Evaluating the safety of Connected and Cooperative Automated Mobility (CCAM) systems—particularly under superhuman capability boundary scenarios—is hindered by the difficulty of matching test scenarios with multi-environment operational capabilities. Method: This paper proposes an automated test case allocation method grounded in a formalized Operational Design Domain (ODD) framework. We innovatively extend the ODD model by integrating critical test attributes—including sensor perception limits and environmental dynamism—to establish a logically inferable environment-adaptation mechanism. Through parameterized ODD modeling, attribute-aware integration, and automated logical inference, our approach enables precise capability–scenario alignment across heterogeneous testing environments. Results: Validated on an autonomous truck reverse-parking function, the method significantly improves test coverage, allocation efficiency, and result consistency. It establishes a new paradigm for CCAM safety assessment that is formally specified, reproducible, and scalable.

Technology Category

• Planning, Routing, and Scheduling: Model-Based Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

The emergence of Connected, Cooperative, and Automated Mobility (CCAM) systems has significantly transformed the safety assessment landscape. Because they integrate automated vehicle functions beyond those managed by a human driver, new methods are required to evaluate their safety. Approaches that compile evidence from multiple test environments have been proposed for type-approval and similar evaluations, emphasizing scenario coverage within the systems Operational Design Domain (ODD). However, aligning diverse test environment requirements with distinct testing capabilities remains challenging. This paper presents a method for evaluating the suitability of test case allocation to various test environments by drawing on and extending an existing ODD formalization with key testing attributes. The resulting construct integrates ODD parameters and additional test attributes to capture a given test environments relevant capabilities. This approach supports automatic suitability evaluation and is demonstrated through a case study on an automated reversing truck function. The system's implementation fidelity is tied to ODD parameters, facilitating automated test case allocation based on each environments capacity for object-detection sensor assessment.

Problem

• Methodology for test case allocation in CCAM safety assessment
• Aligning test environment requirements with testing capabilities
• Automated suitability evaluation for test environments using ODD formalization

Innovation

• Extends ODD formalization with key testing attributes
• Integrates ODD parameters with test environment capabilities
• Enables automated test case allocation for sensor assessment