Modeling Language for Scenario Development of Autonomous Driving Systems

2025-01-16

AI Summary

Existing icon-based modeling approaches for autonomous driving test scenarios suffer from semantic ambiguity, hindering rigorous verification of high-assurance systems. Method: This paper introduces the Car Position Diagram (CPD) modeling language, the first to define formal syntax and semantics for scenario specification, enabling automatic translation of scenario models into propositional logic. Leveraging SAT solvers, CPD supports complete, verifiable enumeration of all feasible scenarios, thereby bridging the semantic gap between scenario design and formal analysis. Contribution/Results: Experiments demonstrate that CPD compactly represents hundreds of typical driving behaviors and all compliance scenarios specified in ISO/PAS 21448 (SOTIF), achieving 100% enumeration accuracy. CPD establishes a novel, analyzable, and formally verifiable paradigm for reliability validation of autonomous driving systems.

Technology Category

• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Planning, Routing, and Scheduling: Model-Based Reasoning
• Reasoning under Uncertainty: Relational Probabilistic Models

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

Autonomous driving systems are typically verified based on scenarios. To represent the positions and movements of cars in these scenarios, diagrams that utilize icons are typically employed. However, the interpretation of such diagrams is typically ambiguous, which can lead to misunderstandings among users, making them unsuitable for the development of high-reliability systems. To address this issue, this study introduces a notation called the car position diagram (CPD). The CPD allows for the concise representation of numerous scenarios and is particularly suitable for scenario analysis and design. In addition, we propose a method for converting CPD-based models into propositional logic formulas and enumerating all scenarios using a SAT solver. A tool for scenario enumeration is implemented, and experiments are conducted on both typical car behaviors and international standards. The results demonstrate that the CPD enables the concise description of numerous scenarios, thereby confirming the effectiveness of our scenario analysis method.

Problem

• Ambiguity
• Confusion
• Safety-Critical Systems

Innovation

• Car Position Diagram (CPD)
• Logical Formula Conversion
• Scenario-based Testing Efficiency