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

Development and evaluation of a human machine interface to support mode awareness in different automated driving modes

“…The concurrent think-aloud method has been demonstrated to validly provide insight into participants' thinking (Charters, 2003) and has been recommended as a way to gain insight into the experience of a design when using the RITE method (Medlock et al, 2005). Moreover, this procedure has proved to be effective in gaining insight into the understandability and usability of information communicated by HMI design in a previous study by Tinga et al (2022).…”

“…In this way, only applicable items were answered by the participants. This approach is applied more often in research (e.g., Hart, 2006;Tinga et al, 2022;Tjon et al, 2019). Regarding the NASA-TLX, three items on mental demand, temporal demand and frustration level were selected.…”

“…Regarding the NASA-TLX, three items on mental demand, temporal demand and frustration level were selected. Regarding the ITC-SOPI, five items on spatial presence were selected, omitting the items of the spatial presence scale focusing on physical interaction, following Tinga et al (2022) and Tjon et al (2019). In this way, items were excluded which do not apply to a passive task such as receiving information through HMI design.…”

“…It was concluded that most implementations are in essence a binary 'on versus off'. However, ensuring mode awareness in multiple automation modes could enable drivers to better comprehend and take on their role in the different modes (Tinga et al, 2022). Approval was recently obtained for an SAE Level 3 system in Germany, the Mercedes traffic jam assist, which takes over the driving task in highway traffic jam situations (Templeton, 2021).…”

An Empirical Study on the Influence of Smart Home Interface Design on the Interaction Performance of the Elderly

“…The experiment uses a scenario-based design approach, a smart scene panel as the interaction center, and a fusion of multimodal interaction to investigate both functional and visual perspectives based on the demand characteristics of elderly users [ 23 ]. Integrating scenario theory with user research, we obtain user behavior, pain points, needs, demand priorities and design opportunity points by building objective scenarios, and finally transform them into age-friendly smart home system functions and an age-friendly interaction interface design, verify the usability and age-appropriateness of the design by building test scenarios, discover the shortcomings of the design, and make improvement iterations.…”