Use Cases for Assessing, Testing, and Validating the Human Machine Interface of Automated Driving Systems. (September 2018)

• Record Type: Journal Article
• Authors: Naujoks, Frederik; Hergeth, Sebastian; Wiedemann, Katharina; Schömig, Nadja; Keinath, Andreas
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 62:Part 1(2018)
• Page Start: 1873
• Page End: 1877
• Publication Date: 2018-09
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1541931218621426
• Languages: English
• ISSNs: 1541-9312

Abstract

Reflecting the increasing demand for harmonization of human machine interfaces (HMI) of automated vehicles, different taxonomies of use cases for investigating automated driving systems (ADS) have been proposed. Existing taxonomies tend to serve specific purposes such as categorizing transitions between automation modes; however, they cannot be generalized to different systems or combinations of systems. In particular, there is no exhaustive set of use cases that allows entities to assess and validate the HMI of a given ADS that takes into account all possible system modes and transitions. The present paper describes a newly developed framework based on combinatorics of SAE (Society of Automotive Engineers) automation levels that incorporates a comprehensive taxonomy of use cases required for the assessment and validation of ADS HMIs. This forms a much-needed basis for test methods required to verify whether an HMI meets minimum requirements such as those outlined in the National Highway Traffic Safety Administration's Federal Automated Vehicles policy.