With an increasing degree of automation, automated vehicle systems become more complex in terms of functional components as well as interconnected hardware and software components. Thus, holistic systems engineering becomes a severe challenge. Emergent properties like system safety are not solely arguable in singular viewpoints such as structural representations of software or electrical wiring (e.g. fault tolerant). This states the need to get several viewpoints on a system and describe correspondences between these views in order to enable traceability of emergent system properties. Today, the most abstract view found in architecture frameworks is a logical description of system functions which structures the system in terms of information flow and functional components. In this article we extend established system viewpoints towards a capability-based assessment of an automated vehicle and conduct an exemplary safety analysis to derive behavioral safety requirements. These requirements can afterwards be attributed to different viewpoints in an architecture frameworks and thus be integrated into a development process for automated vehicles.
Part I of this paper proposed a development process and a system platform for the development of autonomous cars based on a distributed system architecture. The proposed development methodology enabled the design and development of an autonomous car with benefits such as a reduction in computational complexity, fault-tolerant characteristics, and system modularity. In this paper (Part II), a case study of the proposed development methodology is addressed by showing the implementation process of an autonomous driving system. In order to describe the implementation process intuitively, core autonomous driving algorithms (localization, perception, planning, vehicle control, and system management) are briefly introduced and applied to the implementation of an autonomous driving system. We are able to examine the advantages of a distributed system architecture and the proposed development process by conducting a case study on the autonomous system implementation. The validity of the proposed methodology is proved through the autonomous car A1 that won the 2012 Autonomous Vehicle Competition in Korea with all missions completed.