Application of STPA for the Elicitation of Safety Requirements for a Machine Learning-Based Perception Component in Automotive

Celik, Esra Acar; Cârlan, Carmen; Abdulkhaleq, Asim; Bauer, Fridolin; Schels, Martin; Putzer, Henrik J.

doi:10.1007/978-3-031-14835-4_21

Cited by 6 publications

(6 citation statements)

References 10 publications

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“…However, UCAs in both references are defined at the component or subsystem level. Our experience shows that UCA identification is related to activities in functional or technical safety concepts, depending on the abstraction level as also suggested by Celik et al [7].…”

Section: Resultssupporting

confidence: 70%

“…This is one of the reasons why there are differences in literature regarding the mapping of STPA to activities in the automotive process. For instance, NHTSA [13] and SAE J3187 [3] mapped the identification of unsafe control actions (UCAs) to SOTIF hazard identification, however, Celik et al took a different approach and mapped it to the safety concept [7].…”

Section: Resultsmentioning

confidence: 99%

“…In each iteration, all involved parties need to perform an impact analysis to ensure that changes in the new components do not affect their subsystem. For instance, in a study focused on safety requirements for a machine learning-based perception component [7], irrelevant subsystems such as the human-machine interface and actuators are also involved, which can distract the focus of analysis even if all relevant experts and teams are already involved. Additionally, full technical transparency is required in such a setup, which may not always be possible, especially in commercial projects and, as also mentioned by a participant in our interview study, only be possible for "open source projects".…”

Section: Resultsmentioning

confidence: 99%

“…Koelln et al [6] applied STPA on an abstract AD architecture and analyzed the interaction of stakeholders like driver, legislature, and producer during Minimum Risk Maneuver. As part of the "KI Absicherung -Safe AI for Automated Driving" project, Celik et al in [7] investigate the use of the STPA approach for safety requirements elicitation in a Machine Learning based pedestrian collision avoidance system. Abdulkhaleq et al [8] proposed an approach to integrate STPA into the software engineering process and raised the importance of using new methods like STPA over traditional methods like Fault Tree Analysis (FTA).…”

Section: Related Workmentioning

confidence: 99%

“…Based on our best knowledge and a thorough review of the literature, we have not come across any examples of analyses that were performed solely on a subsystem without modeling the rest of the system. Even in cases where the focus of the study is on a particular subsystem, such as the "Machine Learning-Based Perception" subsystem (or component) in [7], all involved systems in the control structure must be included, as required by the instruction of the control structure.…”

Section: Challenge 4-subsystem Supplier Cannot Model the Whole Item (...mentioning

confidence: 99%

See 4 more Smart Citations

On STPA for Distributed Development of Safe Autonomous Driving: An Interview Study

Nouri,

Berger,

Törner

2023

2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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Safety analysis is used to identify hazards and build knowledge during the design phase of safety-relevant functions. This is especially true for complex AI-enabled and software intensive systems such as Autonomous Drive (AD). System-Theoretic Process Analysis (STPA) is a novel method applied in safetyrelated fields like defense and aerospace, which is also becoming popular in the automotive industry. However, STPA assumes prerequisites that are not fully valid in the automotive system engineering with distributed system development and multiabstraction design levels. This would inhibit software developers from using STPA to analyze their software as part of a bigger system, resulting in a lack of traceability. This can be seen as a maintainability challenge in continuous development and deployment (DevOps). In this paper, STPA's different guidelines for the automotive industry, e.g. J31887/ISO21448/STPA handbook, are firstly compared to assess their applicability to the distributed development of complex AI-enabled systems like AD. Further, an approach to overcome the challenges of using STPA in a multilevel design context is proposed. By conducting an interview study with automotive industry experts for the development of AD, the challenges are validated and the effectiveness of the proposed approach is evaluated.

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Section: Resultssupporting

confidence: 70%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Challenge 4-subsystem Supplier Cannot Model the Whole Item (...mentioning

confidence: 99%

See 3 more Smart Citations

On STPA for Distributed Development of Safe Autonomous Driving: An Interview Study

Nouri,

Berger,

Törner

2023

2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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How mature is requirements engineering for AI-based systems? A systematic mapping study on practices, challenges, and future research directions

Habiba,

Haug,

Bogner

et al. 2024

Requirements Eng

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Artificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.

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A system-theoretic assurance framework for safety-driven systems engineering

Ahlbrecht,

Sprockhoff,

Durak

2024

Softw Syst Model

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The complexity of safety-critical systems is continuously increasing. To create safe systems despite the complexity, the system development requires a strong integration of system design and safety activities. A promising choice for integrating system design and safety activities are model-based approaches. They can help to handle complexity through abstraction, automation, and reuse and are applied to design, analyze, and assure systems. In practice, however, there is often a disconnect between the model-based design and safety activities. At the same time, there is often a delay until recent approaches are available in model-based frameworks. As a result, the advantages of the models are often not fully utilized. Therefore, this article proposes a framework that integrates recent approaches for system design (model-based systems engineering), safety analysis (system-theoretic process analysis), and safety assurance (goal structuring notation). The framework is implemented in the systems modeling language (SysML), and the focus is placed on the connection between the safety analysis and safety assurance activities. It is shown how the model-based integration enables tool assistance for the systematic creation, analysis, and maintenance of safety artifacts. The framework is demonstrated with the system design, safety analysis, and safety assurance of a collision avoidance system for aircraft. The model-based nature of the design and safety activities is utilized to support the systematic generation, analysis, and maintenance of safety artifacts.

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Application of STPA for the Elicitation of Safety Requirements for a Machine Learning-Based Perception Component in Automotive

Cited by 6 publications

References 10 publications

On STPA for Distributed Development of Safe Autonomous Driving: An Interview Study

On STPA for Distributed Development of Safe Autonomous Driving: An Interview Study

How mature is requirements engineering for AI-based systems? A systematic mapping study on practices, challenges, and future research directions

A system-theoretic assurance framework for safety-driven systems engineering

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