Automotive Software Engineering

Schäuffele, Jörg; Zurawka, Thomas

doi:10.1007/978-3-322-91947-2

Cited by 24 publications

(15 citation statements)

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“…Technically, the development follows a systems engineering approach which breaks down the system requirements to subsystem and component levels, of which the functionality and properties are directly derived from those of the preceding system level. On each of them, logical, behavioral and technical models are created that correspond to a set of test cases for the future integration task on that level (see: [35]). This process is widely known as the "V-model".…”

Section: Development Processes As a Measure For More Safety And Reliamentioning

confidence: 99%

“…This paper will prove, that this design process can be integrated in today's automotive development schemes. We decided to pick up the so called "core process for system and software development" (CPSSD) published by Schäuffele and Zurawka in [35]. It is a well established model for system development in the automotive industry basing on the popular V-model approach.…”

Section: Self-adaptive Automotive Systemsmentioning

confidence: 99%

“…In this sense we restrict the rest of the paper to the left arm of the "V". According to [35] the first activity of CPSSD is to specify the so called Logical System Architecture (LSA). The LSA is an abstract architecture that does not provide any technical details.…”

Section: The Core Process For System and Software Developmentmentioning

confidence: 99%

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Developing self-adaptive automotive systems

Wagner

Meroth

Zöbel

2013

Des Autom Embed Syst

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Future Driving Assistance Systems (DAS) will have to react to changes within the system at runtime. This might be the case in Car-to-X systems where the availability of communication partners changes dynamically. Another example are systems like DAS for truck and trailer combinations where a trailer might be disconnected and replaced by another one several times a day. State-of-the-art DAS are not capable of handling these runtime changes. In our approach we make usage of the principles of Service-orientation to generate self-adaptive DAS on architectural level. But this technical approach requires the definition of a development process that fits into the practices within the automotive industry. This paper introduces SOMA4DDAS, a model-based development process based on the UML profile SoaML. SOMA4DDAS describes a tri-phase procedure to transfer an idea for a DAS into a detailed specification of the application and the Services involved. These phases are integrated into the "core process for system and software development" (CPSSD), a standard process within the automotive industry. The paper illustrates the benefits of this approach by developing a truck and trailer DAS consisting of 13 different Services.

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Section: Development Processes As a Measure For More Safety And Reliamentioning

confidence: 99%

Section: Self-adaptive Automotive Systemsmentioning

confidence: 99%

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Developing self-adaptive automotive systems

Wagner

Meroth

Zöbel

2013

Des Autom Embed Syst

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“…The complexity 1 of the utilized embedded software increased about fiftyfold within 15 years (Ebert and Jones, 2009). Currently the development phase for new vehicles is estimated to be about three years (Schäuffele and Zurawka, 2010). Increased use of virtual prototyping methods has the potential to further curb the required development time span.…”

Section: Introductionmentioning

confidence: 99%

Towards Qualifiable Code Generation from a Clocked Synchronous Subset of Modelica

Thiele¹,

Knoll²,

Fritzson³

2015

MIC

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So far no qualifiable automatic code generators (ACGs) are available for Modelica. Hence, digital control applications can be modeled and simulated in Modelica, but require tedious additional efforts (e.g., manual reprogramming) to produce qualifiable target system production code. In order to more fully leverage the potential of a model-based development (MBD) process in Modelica, a qualifiable automatic code generator is needed.Typical Modelica code generation is a fairly complex process which imposes a huge development burden to any efforts of tool qualification. This work aims at mapping a Modelica subset for digital control function development to a well-understood synchronous data-flow kernel language. This kernel language allows to resort to established compilation techniques for data-flow languages which are understood enough to be accepted by certification authorities.The mapping is established by providing a translational semantics from the Modelica subset to the synchronous data-flow kernel language. However, this translation turned out to be more intricate than initially expected and has given rise to several interesting issues that require suitable design decisions regarding the mapping and the language subset.

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“…Nevertheless, car manufacturers and the associated supplying industry are aiming at adding further functionality to Electronic Control Units (ECUs) which increases complexity as well as required processing performance (Deubzer et al, 2010;Schäuffele and Zurawka, 2010). Moreover, they intend to decrease the number of ECUs in order to save space and reduce weight.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Validation of AUTOSAR Models

Kienberger

Minnerup

Kuntz

et al. 2014

Proceedings of the 2nd International Conference on Model-Driven Engineering and Software Development

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Abstract:As the rise of single-core processing power is exhausted due to technical limitations, the automotive branch is forced to migrate its control unit software to architectures that feature multiple Independent Execution Units (IEUs). This policy shift brings along new problems resulting from the tremendously increased complexity of such systems. Facing these challenges, software engineers have to cope with possible data inconsistencies caused by, e.g., race conditions or cycles. Being an important and standardized software architecture for electronic control units, the Automotive Open System Architecture (AUTOSAR) provides the basis for tools that support the complexity handling when migrating to architectures with multiple IEUs. Our concept is realized by a tool that executes data dependency analyses directly on AUTOSAR models, determines critical dependencies, automatically solves trivial problems and provides semi-automatic resolution of advanced conflicts.To support the actual parallelization of the system, the tool additionally determines groups of executable units that are suitable to run on a common IEU. This appreciably facilitates the validation of AUTOSAR models and the search for a good mapping of the processing tasks to IEUs.

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Automotive Software Engineering

Cited by 24 publications

References 0 publications

Developing self-adaptive automotive systems

Developing self-adaptive automotive systems

Towards Qualifiable Code Generation from a Clocked Synchronous Subset of Modelica

Analysis and Validation of AUTOSAR Models

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