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Modeling context-aware and intention-aware in-car infotainment systems

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Abstract

It is fundamental to understand users’ intentions to support them when operating a computer system with a dynamically varying set of functions, e.g., within an in-car infotainment system. The system needs to have sufficient information about its own and the user’s context to predict those intentions. Although the development of current in-car infotainment systems is already model-based, explicitly gathering and modeling contextual information and user intentions is currently not supported. However, manually creating software that understands the current context and predicts user intentions is complex, error-prone and expensive. Model-based development can help in overcoming these issues. In this paper, we present an approach for modeling a user’s intention based on Bayesian networks. We support developers of in-car infotainment systems by providing means to model possible user intentions according to the current context. We further allow modeling of user preferences and show how the modeled intentions may change during run-time as a result of the user’s behavior. We demonstrate feasibility of our approach using an industrial case study of an intention-aware in-car infotainment system. Finally, we show how modeling of contextual information and modeling user intentions can be combined by using model transformation.

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Notes

  1. A detailed discussion of the term context can be found in [7].

  2. BMA (Bayes Mean Averaged) estimator as implemented in Weka.

  3. http://www.cs.cmu.edu/~javabayes/Home/.

  4. http://www.cs.waikato.ac.nz/ml/weka/.

  5. As our approach currently requires the modeler to know possible user intentions during modeling time, the system is not able to predict a probability for a certain telephone number but for a certain contact from favorites.

  6. The dataset was stored using the Attribute-Relation File Format (ARFF) (http://www.cs.waikato.ac.nz/ml/weka/arff.html).

  7. A rectangular box represents a task. A rectangular box with a bent upper right corner represents a document. A rectangular box with a bent upper right corner surrounded by a dotted line represents multiple documents. Arrows represent the work flow.

  8. Model-to-Model Transformation Web site: https://projects.eclipse.org/projects/modeling.mmt.

  9. Eclipse Modeling Project Website: https://projects.eclipse.org/projects/modeling.

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Authors and Affiliations

  1. Volkswagen AG, Letterbox 011/17770, 38440, Wolfsburg, Germany

    Daniel Lüddecke & Jens Schneider

  2. Technische Universiät Braunschweig, 38106, Braunschweig, Germany

    Christoph Seidl & Ina Schaefer

Authors
  1. Daniel Lüddecke
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  2. Christoph Seidl
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  3. Jens Schneider
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  4. Ina Schaefer
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Correspondence to Daniel Lüddecke.

Additional information

Communicated by Dr. Jordi Cabot and Alexander Egyed.

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Lüddecke, D., Seidl, C., Schneider, J. et al. Modeling context-aware and intention-aware in-car infotainment systems. Softw Syst Model 17, 973–987 (2018). https://doi.org/10.1007/s10270-016-0543-z

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