Addressing model complexity in automotive system development: Selection of system model elements for allocation of requirements

Modern automotive embedded systems are developed by Original Equipment Manufacturers (OEM) together with multiple suppliers. A key problem for a supplier is to allocate an OEM's requirements specification to their own subsystem design. This is a difficult manual task especially on complex systems and it requires expert knowledge about the system design. To address this problem, this paper presents a design science research to develop and evaluate a Requirements Allocation Assistant tool (RAA). The tool provides functionality to search through and filter requirements and system models to enable efficient requirements allocation even in the presence of complexity. RAA is built on top of the EATOP/Eclipse framework using EAST-ADL as system modelling language. The tool was evaluated and validated during a qualitative usability study with 17 engineers active in the Swedish automotive industry. Key findings are that searching is used to learn about a system, whereas filtering is used to narrow down a set of candidate elements of the system design. Engineers request further support in narrowing down a set of candidate elements and in checking that an allocation is correct.