Development of the 2nd Edition of the ISO 26262

Grießnig, Gerhard; Schnellbach, Adam

doi:10.1007/978-3-319-64218-5_44

Cited by 8 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The current version of IEC 61508 is not applicable for the verification of NN-based SCCS because AI technologies are not recommended there. The latest version of ISO 26262 and its extension, ISO/PAS 21448, which is also known as safety of the intended functionality (SOTIF) [46], will likely provide a way to handle the development of autonomous vehicles. However, SOTIF will only provide guidelines associated with SAE Level 0-2 autonomous vehicles [47], which are not ready for the verification of NN-based autonomous vehicles.…”

Section: Testing and Verification Of Safety-critical Control Softwarementioning

confidence: 99%

“…Taking the automotive industry as an example, several traditional car makers (e.g., GM, BMW, and Toyota) and some high technology companies (e.g., Waymo and Baidu) are leading the revolution in autonomous driving safety. In this section, we first discuss industry practices on the safety of the intended functionality [46]; then, we compare this SLR with related works. At the end of this section, we present the threats to the validity of our study.…”

Section: Industry Practicementioning

confidence: 99%

See 1 more Smart Citation

Testing and verification of neural-network-based safety-critical control software: A systematic literature review

Zhang

2020

Information and Software Technology

View full text Add to dashboard Cite

Context: Neural Network (NN) algorithms have been successfully adopted in a number of Safety-Critical Cyber-Physical Systems (SCCPSs). Testing and Verification (T&V) of NN-based control software in safety-critical domains are gaining interest and attention from both software engineering and safety engineering researchers and practitioners. Objective: With the increase in studies on the T&V of NN-based control software in safety-critical domains, it is important to systematically review the state-of-the-art T&V methodologies, to classify approaches and tools that are invented, and to identify challenges and gaps for future studies. Method: By searching the six most relevant digital libraries, we retrieved 950 papers on the T&V of NN-based Safety-Critical Control Software (SCCS). Then we filtered the papers based on the predefined inclusion and exclusion criteria and applied snowballing to identify new relevant papers. Results: To reach our result, we selected 83 primary papers published between 2001 and 2018, applied the thematic analysis approach for analyzing the data extracted from the selected papers, presented the classification of approaches, and identified challenges. Conclusion: The approaches were categorized into five high-order themes: assuring robustness of NNs, assuring safety properties of NN-based control software, improving the failure resilience of NNs, measuring and ensuring test completeness, and improving the interpretability of NNs. From the industry perspective, improving the interpretability of NNs is a crucial need in safetycritical applications. We also investigated nine safety integrity properties within four major safety lifecycle phases to investigate the achievement level of T&V goals in IEC 61508-3. Results show that correctness, completeness, freedom from intrinsic faults, and fault tolerance have drawn most attention from the research community. However, little effort has been invested in achieving repeatability; no reviewed study focused on precisely defined testing configuration or on defense against common cause failure.

show abstract

Section: Testing and Verification Of Safety-critical Control Softwarementioning

confidence: 99%

Section: Industry Practicementioning

confidence: 99%

Testing and verification of neural-network-based safety-critical control software: A systematic literature review

Zhang

2020

Information and Software Technology

View full text Add to dashboard Cite

show abstract

“…One challenge of using the safety case approach is arguing that the evidence is sufficient to ensure safety of the system. The forthcoming version of ISO 26262:2018 and its extension, ISO/PAS 21448, which is also known as SOTIF (Safety of the Intended Functionality) [10], will likely provide a way to handle the development of autonomous vehicles. But SOTIF will only provide guidelines for Level 0-2 autonomous vehicles [11], which are not designed for the validation of deep-learning-based autonomous vehicles.…”

Section: Some Approaches To Analyzing Safety Of Autonomous Vehiclesmentioning

confidence: 99%

Could We Issue Driving Licenses to Autonomous Vehicles?

Zhang

Kaloudi

2018

Developments in Language Theory

View full text Add to dashboard Cite

Many companies are studying autonomous vehicles. One trend in the development of control algorithms for autonomous vehicles is the use of deep-learning approaches. The general idea is to simulate a human driver's decision-making and behavior in various scenarios without necessarily knowing why the decision is made. In this position paper, we first argue that traditional safety analysis methods need to be extended to verify deep-learning-based autonomous vehicles. Then, we propose borrowing ideas from the process of issuing driving licenses to human drivers to verify autonomous vehicles. Verification of autonomous vehicles could focus on sufficient training as well as mental and physical health checks. Based on this position, we list several challenges that need to be addressed.

show abstract

Speed-Up Testing by Application of Semiformal Notations and Automation

Ringdorfer

Grießnig

2021

Communications in Computer and Information Science

View full text Add to dashboard Cite

Development of the 2nd Edition of the ISO 26262

Cited by 8 publications

References 0 publications

Testing and verification of neural-network-based safety-critical control software: A systematic literature review

Testing and verification of neural-network-based safety-critical control software: A systematic literature review

Could We Issue Driving Licenses to Autonomous Vehicles?

Speed-Up Testing by Application of Semiformal Notations and Automation

Contact Info

Product

Resources

About