Home > Archive > 2011 > Volume 1 Number 4 (Oct. 2011) >
IJMLC 2011 Vol.1(4): 359-365 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2011.V1.53

An adaptive Software and Systems Architecture for Driver Assistance Systems based on service orientation

M. Wagner, D. Zöbel and A. Meroth

Abstract—State of the art automotive software systems presume a static configuration of electronic control units and software components. Assuming that future Driver Assistance Systems (DAS) will deploy dynamically changing software configurations, the authors propose an approach towards an adaptive software and systems architecture for DAS. The paper focuses on systems, which assist the driver while backing up truck and trailer combinations. These systems are characterized by a high degree of distribution as well as a high level of heterogeneity and changeability even at runtime. In order to meet these demands, the authors suggest the usage of service orientation combined with software agents. The functional units of these systems are encapsulated in services which are dynamically orchestrated by the agents whenever the system changes. This paper describes the ideas of this approach using a real world example. It also names and classifies the scenarios of re-configuration. The article concludes with a lookout on the future work within this project.

Index Terms—automotive software architecture, automotive systems architecture, driver assistance systems, re-configuration, service oriented architecture, software agents

Marco Wagner and Ansgar Meroth are with the faculty of Mechanics and Electronics, Heilbronn University, Heilbronn, Germany. (e-mail: Marco.Wagner@hs-heilbronn.de). (e-mail: Ansgar.Meroth@hs-heilbronn.de). Dieter Zöbel is with the faculty of Computer Science of the University of Koblenz-Landau, Koblenz, Germany (e-mail: Zoebel@uni-koblenz.de).

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Cite: M. Wagner, D. Zöbel and A. Meroth, "An adaptive Software and Systems Architecture for Driver Assistance Systems based on service orientation," International Journal of Machine Learning and Computing vol. 1, no. 4, pp.359-365, 2011.

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net


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