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Human machine interface design for continuous support of mode awareness during automated driving: An online simulation

任务(项目管理) 预测(人工智能) 自动化 计算机科学 人机交互 模式(计算机接口) 可靠性(半导体) 会话(web分析) 接口(物质) 人机系统 形势意识 模拟 工程类 系统工程 万维网 人工智能 操作系统 机械工程 功率(物理) 物理 气泡 量子力学 最大气泡压力法 航空航天工程
作者
Angelica M. Tinga,Diane Cleij,Reinier J. Jansen,Sander van der Kint,Nicole van Nes
出处
期刊:Transportation Research Part F-traffic Psychology and Behaviour [Elsevier]
卷期号:87: 102-119 被引量:12
标识
DOI:10.1016/j.trf.2022.03.020
摘要

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.
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