Block-Based Platform for Defining Adaptation Rules for Automotive Systems

Adaptive human-machine interfaces (HMIs) enhance driver safety and comfort by tailoring information presentation. While existing research identifies key adaptation parameters, their practical application remains challenging due to the complexity of rule-based decision making and the limitations of current authoring tools. To address these issues, this paper introduces AHSL, a domain-specific language for efficiently specifying message adaptation logic. By unifying established adaptation parameters within a hierarchical structure, AHSL simplifies rule creation and improves readability. Usability testing demonstrates AHSL's effectiveness in supporting intuitive and efficient decision logic development.

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Published
2024-10-17
DOI
https://doi.org/10.1145/3689488.3689989
Primary Topic
Model-Driven Software Engineering Techniques
Type
article
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article

Block-Based Platform for Defining Adaptation Rules for Automotive Systems

Ion Barosan, Mauricio Verano Merino, Luigi Altamirano
Model-Driven Software Engineering Techniques
article

Block-Based Platform for Defining Adaptation Rules for Automotive Systems

Ion Barosan, Mauricio Verano Merino, Luigi Altamirano
article en

Abstract

Adaptive human-machine interfaces (HMIs) enhance driver safety and comfort by tailoring information presentation. While existing research identifies key adaptation parameters, their practical application remains challenging due to the complexity of rule-based decision making and the limitations of current authoring tools. To address these issues, this paper introduces AHSL, a domain-specific language for efficiently specifying message adaptation logic. By unifying established adaptation parameters within a hierarchical structure, AHSL simplifies rule creation and improves readability. Usability testing demonstrates AHSL's effectiveness in supporting intuitive and efficient decision logic development.

Eindhoven University of Technology (NL), Vrije Universiteit Amsterdam (NL)
Openalex Percentile: Top 81%
Model-Driven Software Engineering Techniques
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