Human machine interface design for continuous support of mode awareness during automated driving: An online simulation. (May 2022)

• Record Type: Journal Article
• Authors: Tinga, Angelica M.; Cleij, Diane; Jansen, Reinier J.; van der Kint, Sander; van Nes, Nicole
• Is Part Of: Transportation research. Volume 87(2022)
• Page Start: 102
• Page End: 119
• Publication Date: 2022-05
• Subjects: HMI -- Automated driving -- Mode awareness -- Human factors in vehicle automation -- Think-aloud -- NDRA; Automobile drivers -- Psychology -- Periodicals; Automobile driving -- Psychological aspects -- Periodicals; Transportation -- Psychological aspects -- Periodicals; 629.283019
• DOI: 10.1016/j.trf.2022.03.020
• Languages: English
• ISSNs: 1369-8478

Abstract

Highlights: A Human Machine Interface (HMI) should support the driver during automated driving. This work explores support of supervision and self-regulation through HMI design. Simulated drives with four different HMI designs were presented to participants. Concurrent think-aloud data and questionnaire data were collected. Findings highlight potential of anticipatory and automation reliability information. Abstract: In the transition towards higher levels of vehicle automation, one of the key concerns with regards to human factors is to avoid mode confusion, when drivers misinterpret the driving mode and therewith misjudge their own tasks and responsibility. To enhance mode awareness, a clear human centered Human Machine Interface (HMI) is essential. The HMI should support the driver tasks of both supervising the driving environment when needed and self-regulating their non-driving related activities (NDRAs). Such support may be provided by either presenting continuous information on automation reliability, from which the driver needs to infer what task is required, or by presenting continuous information on the currently required driving task and allowed NDRA directly. Additionally, it can be valuable to provide continuous information to support anticipation of upcoming changes in the automation mode and its associated reliability or required and allowed driver task(s). Information that could support anticipation includes the available time until a change in mode (i.e. time budget), information on the upcoming mode, and reasons for changing to the upcoming mode. The current work investigates the effects of communicating this potentially valuable information through HMI design. Participants received information from an HMI during simulated drives in a simulated car presented online (using Microsoft Teams) with an experimenter virtually accompanying and guiding each session. The HMI either communicated on automation reliability or on the driver task, and either included information supporting anticipation or did not include such information. Participants were thinking aloud during the simulated drives and reported on their experience and preferences afterwards. Anticipatory information supported understanding about upcoming changes without causing information overload or overreliance. Moreover, anticipatory information and information on automation reliability, and especially a combination of the two, best supported understandability and usability. Recommendations are provided for future work on facilitating supervision and NDRA self-regulation during automated driving through HMI design.