SEMar 16, 2018

Model-based Verification and Validation of an Autonomous Vehicle System

arXiv:1803.06103v24 citations
Originality Synthesis-oriented
AI Analysis

This work addresses safety assurance for autonomous vehicle software, but it is incremental as it builds on previous modifications to EAST-ADL.

The paper extended a model-based verification approach for autonomous vehicles by integrating Simulink/Stateflow into a tool-chain to transform models into UPPAAL for formal analysis, and validated it on a traffic sign recognition case study.

The software development for Cyber-Physical Systems (CPS), e.g., autonomous vehicles, requires both functional and non-functional quality assurance to guarantee that the CPS operates safely and effectively. EAST-ADL is a domain specific architectural language dedicated to safety-critical automotive embedded system design. We have previously modified EAST-ADL to include energy constraints and transformed energy-aware real-time (ERT) behaviors modeled in EAST-ADL/STATEFLOW into UPPAAL models amenable to formal verification. Previous work is extended in this paper by including support for SIMULINK and an integration of Simulink/Stateflow within a same tool-chain. Simulink/Stateflow models are transformed, based on extended ERT constraints in EAST-ADL, into verifiable UPPAAL models with stochastic semantics and integrate the translation with formal statistical analysis techniques: Probabilistic extension of EAST-ADL constraints is defined as a semantics denotation. A set of mapping rules is proposed to facilitate the guarantee of translation. Formal analysis on both functional- and non-functional properties is performed using SIMULINK DESIGN VERIFIER/UPPAAL-SMC. The analysis techniques are validated and demonstrated on the autonomous traffic sign recognition vehicle case study.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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