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Human-Machine Interfaces for Automated Driving: Development of an Experimental Design for Evaluating Usability

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Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021) (IEA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 221))

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Abstract

The introduction of conditionally automated driving [25] implies repeated transitions of the driving task between the human operator and the automated driving system (ADS). Human-machine interfaces (HMIs) facilitating these shifts in control are essential. Usability serves as an important criterion to assess the quality of an HMI design. This paper derives a study design for assessing the usability based on the best practice advice by [1]. The paper covers the applied definitions of usability, the sample characteristics, the test cases, the HMIs, the dependent variables, the procedure, the conditions of use, and the testing environment. The study design will be applied in a driving simulator and three test track experiments in different countries within an ongoing project. This involves a number of safety, technical and resource constraints in the development of the study design. This paper describes the challenges and limitations of applying a generic best practice advice to the varying test settings. Furthermore, two HMI concepts are developed and evaluated in an expert assessment. The two concepts will serve as the research subjects in the series of experiments. The proposed study design is suitable for application in different test settings. Therefore, the comparability between the experiments is high. This paper provides a first step in a validation project with the overall goal to propose a practical approach to usability testing of ADS HMIs that covers different constructs of usability and appropriate dependent variables within their application areas.

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Acknowledgement

This work was funded by the BMW Group.

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Authors and Affiliations

  1. Chair of Ergonomics, Technical University of Munich, Boltzmannstr. 15, 85748, Garching, Germany

    Deike Albers, Jonas Radlmayr, Niklas Grabbe & Klaus Bengler

  2. BMW Group, Knorrstr. 147, 80937, Munich, Germany

    Sebastian Hergeth, Frederik Naujoks, Yannick Forster & Andreas Keinath

Authors
  1. Deike Albers
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  2. Jonas Radlmayr
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  3. Niklas Grabbe
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  4. Sebastian Hergeth
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  5. Frederik Naujoks
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  6. Yannick Forster
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  7. Andreas Keinath
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  8. Klaus Bengler
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Corresponding author

Correspondence to Deike Albers .

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Editors and Affiliations

  1. Département de génie mécanique, Université de Moncton, Moncton, NB, Canada

    Nancy L. Black

  2. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, ON, Canada

    W. Patrick Neumann

  3. Toronto, ON, Canada

    Ian Noy

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Albers, D. et al. (2021). Human-Machine Interfaces for Automated Driving: Development of an Experimental Design for Evaluating Usability. In: Black, N.L., Neumann, W.P., Noy, I. (eds) Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021). IEA 2021. Lecture Notes in Networks and Systems, vol 221. Springer, Cham. https://doi.org/10.1007/978-3-030-74608-7_66

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  • DOI: https://doi.org/10.1007/978-3-030-74608-7_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-74607-0

  • Online ISBN: 978-3-030-74608-7

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