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The transportation industry is facing major challenges that come along with innovative trends like autonomous driving. Due to the growing amount of network participants, smart sensors, and mixed-critical data, scalability and interoperability have become key factors of cost-efficient vehicle engineering. One solution to overcome these challenges is the AUTOSAR Adaptive software platform. Its service-oriented communication methodology allows a standardized data exchange that is not bound to a specific middleware protocol. OPC UA is a communication standard that is well-established in modern industrial automation. In addition to its Client–Server communication pattern, the newly released Publish–Subscribe (PubSub) architecture promotes scalability. PubSub is designed to work in conjunction with Time-Sensitive Networking (TSN), a collection of standards that add real-time aspects to standard Ethernet networks. TSN allows services with different requirements to share a single physical network. In this paper, we specify an integration approach of AUTOSAR Adaptive, OPC UA, and TSN. It combines the benefits of these three technologies to provide deterministic high-speed communication. Our main contribution is the architecture for the binding between Adaptive Platform and OPC UA. With a prototypical implementation, we prove that a combination of OPC UA Client–Server and PubSub qualifies as a middleware solution for service-oriented communication in AUTOSAR.

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Increasingly intelligent energy-management and safety systems are developed to realize safe and economic automobiles. The realization of these systems is only possible with complex and distributed software. This development poses a challenge for verification and validation. Upcoming standards like ISO 26262 provide requirements for verification and validation during development phases. Advanced test methods are requested for safety critical functions. Formal specification of requirements and appropriate testing strategies in different stages of the development cycle are part of it. In this paper we present our approach to formalize the requirements specification by test models. These models serve as basis for the following testing activities, including the automated derivation of executable test cases from it. Test cases can be derived statistically, randomly on the basis of operational profiles, and deterministically in order to perform different testing strategies. We have applied our approach with a large German OEM in different development stages of active safety and energy management functionalities. The test cases were executed in model-in-the-loop and in hardware-in-the-loop simulation. Errors were identified with our approach both in the requirement specification and in the implementation that were not discovered before.