Data underlying the publication: Designing User Interfaces for Partially Automated Vehicles: Effects of Information and Modality on Trust and Acceptance
This study aims to identify how user interfaces (UI) can enhance driver's trust and acceptance and reduce perceived risk. Four interfaces were designed with different levels of complexity. These levels were achieved by combining automation information (surrounding information vs surrounding and manoeuvre information) and modality (visual modality vs visual-auditory). These interfaces were evaluated in a driving simulator in which a partially automated vehicle reacted to an event of a merging and braking vehicle in its front. The criticality of the events was manipulated by the factors merging gap (in meters) and deceleration (m/s2) of the vehicle in front. This reaction of the automation was either to brake or to change lanes. The results show that an optimal combination of automation information and modality enhances drivers' trust, communication with automation, perceived ease of use, and perceived usefulness. More specifically, the most complex UI, which provided surrounding and manoeuvre information via the visual and auditory modalities, was associated with the highest trust and acceptance ranking and the lowest perceived risk. Manoeuvre information delivered through the auditory modality was particularly effective in enhancing trust and acceptance. The benefits of the UIs were consistent over events. However, in the most critical events drivers did not feel entirely safe and did not trust the automation completely. This study shows that the design of UIs for partially automated vehicles should include surrounding and manoeuvre information combining visual and auditory modalities.
- 2023-04-17 first online
- 2023-10-13 published, posted
- Horizon 2020 - HADRIAN (grant code 875597) [more info...] European research council
- Horizon 2020 - SHAPE-IT (grant code 860410) European Union’s Horizon 2020