Search Results

Future automotive systems will be connected with other vehicles and information systems for improved road safety, mobility and comfort. This new connectivity establishes data and command channels between the internal automotive system and arbitrary external entities. One significant issue of this paradigm shift is that formerly closed automotive systems now become open systems that can be maliciously influenced through their communication interfaces. This introduces a new class of security challenges for automotive design. It also indirectly impacts the safety mechanisms that rely on a closed-world assumption for the vehicle. We present a new security analysis approach that helps to identify and prioritize security issues in automotive architectures. The methodology incorporates a new threat classification for data flows in connected vehicle systems.

In-vehicle communication faces increasing bandwidth demands, which can no longer be met by today's MOST150, FlexRay or CAN networks. In recent years, Fast Ethernet has gained a lot of momentum in the automotive world, because it promises to bridge the bandwidth gap. A first step in this direction is the introduction of Ethernet as an On Board Diagnostic (OBD) interface for production vehicles. The next potential use cases include the use of Ethernet in Driver Assistance Systems and in the infotainment domain. However, for many of these use cases, the Fast Ethernet solution is too slow to move the huge amount of data between the Domain Controllers, ADAS Systems, Safety Computer and Chassis Controller in an adequate way. The result is the urgent need for a network technology beyond the Fast Ethernet solution. The question is: which innovation will provide enough bandwidth for domain controllers, fast flashing routines, video data, MOST-replacement and internal ECU buses?

This paper presents the further development, implementation and evaluation of a computer-aided engineering (CAE) method for tool-independent simulation model coupling with a function-based modular framework for entire-system simulations. For that purpose, the preliminary findings regarding the development process of the function-based modular framework are presented. Emanating from that, a hierarchical structure for consistent data distribution and deposition for separating the system to be simulated is introduced. Therein the boundaries of the subsystems are defined, to avoid overlapping and ensuring a consistent ratio of the subsystems. Thus, the exchangeability and the reuse of simulation models are supported. Additionally, a scheme for signal names of the subsystems interfaces is described to allow general interoperability between the subsystems within the function-based modular framework.

New technologies such as multi-core and Ethernet provide vastly improved computing and communications capabilities. This sets the foundation for the implementation of new digital megatrends in almost all areas: driver assistance, vehicle dynamics, electrification, safety, connectivity, autonomous driving. The new challenge: We must share these computing and communication capacities among all vehicle functions and their software. For this step, we need a good resource planning to minimize the probability of late resource bottlenecks (e.g. overload, lack of real-time capability, quality loss). In this article, we summarize the status quo in the field of resource management and provide an outlook on the challenges ahead.

Integration scenarios for ECU software become more complicated, as more constraints with regards to timing, safety and security need to be considered. Multi-core microcontrollers offer even more hardware potential for integration scenarios. To tackle the complexity, more and more model based approaches are used. Understanding the interaction between the different software components, not only from a functional but also from a timing view, is a key success factor for high integration scenarios. In particular for multi-core systems, an amazing amount of timing data can be generated. Usually a multi-core system handles more software functionality than a single-core system. Furthermore, there may be timing interference on the multicore systems, due to the shared usage of buses, memory banks or other hardware resources.