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Article

Engagement in Non-Driving Related Tasks as a Non-Intrusive Measure for Mode Awareness: A Simulator Study

1
BMW Group, Knorrstr. 147, 80937 Munich, Germany
2
Department of Mechanical Engineering, Technical University Munich, Boltzmannstr. 15, 85748 Garching, Germany
*
Author to whom correspondence should be addressed.
Information 2020, 11(5), 239; https://doi.org/10.3390/info11050239
Submission received: 8 April 2020 / Revised: 16 April 2020 / Accepted: 23 April 2020 / Published: 28 April 2020

Abstract

Research on the role of non-driving related tasks (NDRT) in the area of automated driving is indispensable. At the same time, the construct mode awareness has received considerable interest in regard to human–machine interface (HMI) evaluation. Based on the expectation that HMI design and practice with different levels of driving automation influence NDRT engagement, a driving simulator study was conducted. In a 2 × 5 (automation level x block) design, N = 49 participants completed several transitions of control. They were told that they could engage in an NDRT if they felt safe and comfortable to do so. The NDRT was the Surrogate Reference Task (SuRT) as a representative of a wide range of visual–manual NDRTs. Engagement (i.e., number of inputs on the NDRT interface) was assessed at the onset of a respective episode of automated driving (i.e., after transition) and during ongoing automation (i.e., before subsequent transition). Results revealed that over time, NDRT engagement increased during both L2 and L3 automation until stable engagement at the third block. This trend was observed for both onset and ongoing NDRT engagement. The overall engagement level and the increase in engagement are significantly stronger for L3 automation compared to L2 automation. These results outline the potential of NDRT engagement as an online non-intrusive measure for mode awareness. Moreover, repeated interaction is necessary until users are familiar with the automated system and its HMI to engage in NDRTs. These results provide researchers and practitioners with indications about users’ minimum degree of familiarity with driving automation and HMIs for mode awareness testing.
Keywords: automated driving; human-machine interface; mode awareness automated driving; human-machine interface; mode awareness

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MDPI and ACS Style

Forster, Y.; Geisel, V.; Hergeth, S.; Naujoks, F.; Keinath, A. Engagement in Non-Driving Related Tasks as a Non-Intrusive Measure for Mode Awareness: A Simulator Study. Information 2020, 11, 239. https://doi.org/10.3390/info11050239

AMA Style

Forster Y, Geisel V, Hergeth S, Naujoks F, Keinath A. Engagement in Non-Driving Related Tasks as a Non-Intrusive Measure for Mode Awareness: A Simulator Study. Information. 2020; 11(5):239. https://doi.org/10.3390/info11050239

Chicago/Turabian Style

Forster, Yannick, Viktoria Geisel, Sebastian Hergeth, Frederik Naujoks, and Andreas Keinath. 2020. "Engagement in Non-Driving Related Tasks as a Non-Intrusive Measure for Mode Awareness: A Simulator Study" Information 11, no. 5: 239. https://doi.org/10.3390/info11050239

APA Style

Forster, Y., Geisel, V., Hergeth, S., Naujoks, F., & Keinath, A. (2020). Engagement in Non-Driving Related Tasks as a Non-Intrusive Measure for Mode Awareness: A Simulator Study. Information, 11(5), 239. https://doi.org/10.3390/info11050239

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