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Model-Based Design with production code generation has been extensively utilized throughout the automotive software engineering community because of its ability to address complexity, productivity, and quality challenges. With new applications such as lane departure warning or electromechanical steering, engineers have begun to consider Model-Based Design to develop embedded software for applications that need to comply with safety standards such as IEC 61508. For in-vehicle applications, IEC 61508 is often considered state-of-the-art or generally accepted rules of technology (GART) for development of high-integrity software [6, 11]. In order to demonstrate standards compliance, the objectives and recommendations outlined in IEC 61508-3 [8] must be mapped onto processes and tools for Model-Based Design. This paper discusses a verification and validation workflow for developing in-vehicle software components which need to comply with IEC 61508-3 using Model-Based Design.

For many mission critical systems, demonstrating that all requirements have been met via a set of requirements-based tests is often mandated by internal processes or external standards. Traditional coverage approaches, however, do not address this mandate because they measure only the coverage of the design by determining which paths in the design have been executed. Determining whether a given set of test vectors covers the design requirements (as opposed to merely covering the design) is a challenge. Creating a set of test vectors to cover the requirements can be difficult and time consuming. Using techniques first identified in the 1970s and modern Model-Based Design tools, we present a novel approach, based on work presented in [2], to automatically generate a set of requirements-based test vectors. In this paper, we discuss how requirements captured in a natural language can be modeled using Cause-Effect graphs, introduced in [1].

The transition to Model-Based Design must be managed carefully, both to demonstrate short-term benefits and to establish a culture that enables the full realization of the theoretical benefits of this approach. In this paper we introduce the concepts of Model-Based Design, highlight some of its benefits, and then discuss in detail the 10 best practices for adopting a Model-Based Design culture across an organization. These best practices have been gleaned from successful and not-so-successful transformations to Model-Based Design at companies from a variety of different industries.

Many of the multimedia and convenience features in today's passenger vehicles involve Human Machine Interfaces (HMIs), such as the radio face plate or the remote key fob. The functional requirements for these systems are often written in terms of the customer interaction with the interface device. In the past, design engineers would not begin to test requirements for these systems until prototype hardware was available. However, many product development organizations are shifting from this hardware-based traditional development cycle, which relies on designing via a prototype and test iteration, to Model-Based Design. Unfortunately, testing systems with complex human machine interface requirements becomes less intuitive when the prototypes are removed from the design process, because the test cases must be scripted into the modeling environment instead of being applied directly to a prototype of the interface device.

Today, many leading automotive OEMs and Suppliers are adopting Model-Based Design for the development of embedded systems applications. In this paper, the authors review the challenges of performing configuration management that is adequate for use in a production environment of the models and associated files central to Model-Based Design.

Today's vehicles are typically outfitted with passenger convenience features that require Human Machine Interfaces (HMIs). HMIs can be relatively simple - such as a remote key fob - or more sophisticated - such as a radio face plate. Traditional development of HMIs involves two typically independent processes - (1) Physical Component Design and (2) Functional Logic Design. The physical component design is developed by a team that usually includes both graphics and ergonomics designers to ensure that the HMI is intuitive and fits well with the interior styling of the vehicle. The functional logic design follows a more typical software development process. This process is based on functional requirements commonly written in terms of user requests and system responses as represented by the HMI. As the complexity of the system increases, it is essential for the intuitiveness and ease of use of the HMI to advance as well.

Model-Based Design is no longer limited to R&D and pilot programs; it is frequently used for production programs at automotive companies around the world. The demands of production programs drive an even greater need for tools and practices that enable automation and rigor in the area of verification, validation, and test. Without these tools and practices, achieving the quality demanded by the automotive market is not possible. This paper presents best practices in verification, validation, and test that are applicable to any program, but are critical when applying Model-Based Design in production programs.

To provide customers with the latest features, new passenger cars can have more than 50 microprocessors. With this increasing electronic complexity, the process by which the requirements are captured, a design evolves and is verified, becomes increasing critical to the overall success of the design. In this paper, the authors demonstrate how using Model-Based Design with a Systems Engineering approach can address some common failure modes that arise during the traditional automotive design process.