Data-driven development, a complementing approach for automotive systems engineering
| Autor: | Eric Sax, Marc Holzapfel, Johannes Bach, Stefan Otten, Jacob Langner |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
Process (engineering) business.industry Scale (chemistry) Automotive industry Software development 02 engineering and technology Manufacturing engineering Field (computer science) Data-driven Domain (software engineering) 020303 mechanical engineering & transports 0203 mechanical engineering Scalability 0202 electrical engineering electronic engineering information engineering Systems engineering 020201 artificial intelligence & image processing business |
| Zdroj: | 2017 IEEE International Systems Engineering Symposium (ISSE). |
| DOI: | 10.1109/syseng.2017.8088295 |
| Popis: | Established methods and processes in the field of Automotive Systems Engineering (ASE) are challenged by the rising complexity of current features. Expanding system boundaries, tighter interconnections of functional elements, increasingly complex algorithms and an ever growing operational domain generate a multitude of different scenarios that require consideration during specification, design, implementation and testing. This paper reflects the current practice on the example of the Automotive SPICE process reference for system and software development in the automotive domain. It then contemplates on opportunities of consistent usage of recorded vehicle data throughout all phases of automotive development. Our concept of data-driven development is not intended to replace the current practice but to complement it. A summary of our previous work demonstrates the practicability of the concept on the basis of the development of a Predictive Cruise Control (PCC) feature. The contribution concludes with a scalable concept for the large scale application of data-driven development in ASE. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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