Requirement representation for safety critical and fairness aware automotive perception systems - Identifying requirements representation challenges for multi party collaboration.
| dc.contributor.author | Jakobsson, Oskar | |
| dc.contributor.author | Rohacova, Zuzana | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för data och informationsteknik | sv |
| dc.contributor.department | Chalmers University of Technology / Department of Computer Science and Engineering | en |
| dc.contributor.examiner | Penzenstadler, Birgit | |
| dc.contributor.supervisor | Heyn, Hans-Martin | |
| dc.contributor.supervisor | Saeeda, Hina | |
| dc.date.accessioned | 2024-09-10T15:05:42Z | |
| dc.date.available | 2024-09-10T15:05:42Z | |
| dc.date.issued | 2024 | |
| dc.date.submitted | ||
| dc.description.abstract | Background: Advancements in the field of machine learning (ML), have unlocked new capabilities for Driving Automation Systems (DAS). These DAS systems rely on the input from automotive perception systems. These systems exist in a safety critical domain, and well-defined requirements are key to ensure that they can operate safely. However, requirements engineering (RE) for ML-enabled systems has been identified as a challenge in research. Aim: The thesis aimed to investigate current approaches in RE for automotive perception systems, and identify what challenges exist and which processes work well. Specifically, approaches for requirement representations, model kinds, templates, and structures. The thesis also wanted to explore if a shared language, in regards to domain description, reference system architecture, and reference information model, could help mitigate potential challenges without hindering approaches that work well. Methods: An exploratory case study was conducted by interviewing experts in the automotive field. This included participants from a major automotive OEM, suppliers to said OEM and experienced researchers in the automotive field. In total ten interviewees were consulted. Results: The challenges and what works well in the current processes in the case study companies were identified through thematic analysis of the interview data. The thesis explored the potential of a shared language to mitigate these challenges by discussing the topic with interviewees and observing brainstorming workshops for the creation of the shared language. Conclusions: The thesis shows that there is a lack of industry standards in RE for ML-enabled automotive perception systems, which complicates multi-party development. According to interviewees, the shared language has potential to alleviate the identified challenges. However, the feasibility of the shared language is still unclear. | |
| dc.identifier.coursecode | DATX05 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12380/308565 | |
| dc.language.iso | eng | |
| dc.setspec.uppsok | Technology | |
| dc.subject | Requirements engineering | |
| dc.subject | Requirements | |
| dc.subject | Perception systems | |
| dc.subject | Thesis | |
| dc.subject | Requirements representation | |
| dc.subject | Safety-critical | |
| dc.subject | Multi-party development | |
| dc.subject | Automotive | |
| dc.subject | Shared language | |
| dc.title | Requirement representation for safety critical and fairness aware automotive perception systems - Identifying requirements representation challenges for multi party collaboration. | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master's Thesis | en |
| dc.type.uppsok | H | |
| local.programme | Software engineering and technology (MPSOF), MSc |