SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Albers D, Radlmayr J, Loew A, Hergeth S, Naujoks F, Keinath A, Bengler K. Information (Basel) 2020; 11(5): e240.

Copyright

(Copyright © 2020, MDPI: Multidisciplinary Digital Publications Institute)

DOI

10.3390/info11050240

PMID

unavailable

Abstract

The projected introduction of conditional automated driving systems to the market has sparked multifaceted research on human–machine interfaces (HMIs) for such systems. By moderating the roles of the human driver and the driving automation system, the HMI is indispensable in avoiding side effects of automation such as mode confusion, misuse, and disuse. In addition to safety aspects, the usability of HMIs plays a vital role in improving the trust and acceptance of the automated driving system. This paper aggregates common research methods and findings based on an extensive literature review. Empirical studies, frameworks, and review articles are included.

FINDINGS and conclusions are presented with a focus on study characteristics such as test cases, dependent variables, testing environments, or participant samples. These methods and findings are discussed critically, taking into consideration requirements for usability assessments of HMIs in the context of conditional automated driving. The paper concludes with a derivation of recommended study characteristics framing best practice advice for the design of experiments. The advised selection of scenarios and metrics will be applied in a future validation study series comprising a driving simulator experiment and three real driving experiments on test tracks in Germany, the USA, and Japan.


Language: en

Keywords

conditionally automated driving; human–machine interface; method development; usability; validity

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print