Employing a 2x2 within-subjects design, forty-eight experienced drivers (28 male, 20 female) undertook repeated button selection and 'slider-bar' manipulation tasks, to compare a traditional touchscreen with a virtual mid-air gesture interface in a driving simulator. Both interfaces were tested with and without haptic feedback generated using ultrasound. Results show that combining gestures with mid-air haptic feedback was particularly promising, reducing the number of long glances and mean off-road glance time associated with the in-vehicle tasks. For slider-bar tasks in particular, gestures-with-haptics was also associated with the shortest interaction times, highest number of correct responses and least 'overshoots', and was favoured by participants. In contrast, for button-selection tasks, the touchscreen was most popular, enabling the highest accuracy and quickest responses, particularly when combined with haptic feedback to guide interactions, although this also increased visual demand. The study shows clear potential for gestures with mid-air ultrasonic haptic feedback in the automotive domain.
Given the proliferation of 'intelligent' and 'socially-aware' digital assistants embodying everyday mobile technology - and the undeniable logic that utilising voice-activated controls and interfaces in cars reduces the visual and manual distraction of interacting with in-vehicle devices - it appears inevitable that next generation vehicles will be embodied by digital assistants and utilise spoken language as a method of interaction. From a design perspective, defining the language and interaction style that a digital driving assistant should adopt is contingent on the role that they play within the social fabric and context in which they are situated. We therefore conducted a qualitative, Wizard-of-Oz study to explore how drivers might interact linguistically with a natural language digital driving assistant. Twenty-five participants drove for 10 min in a medium-fidelity driving simulator while interacting with a state-of-the-art, high-functioning, conversational digital driving assistant. All exchanges were transcribed and analysed using recognised linguistic techniques, such as discourse and conversation analysis, normally reserved for interpersonal investigation. Language usage patterns demonstrate that interactions with the digital assistant were fundamentally social in nature, with participants affording the assistant equal social status and high-level cognitive processing capability. For example, participants were polite, actively controlled turn-taking during the conversation, and used back-channelling, fillers and hesitation, as they might in human communication. Furthermore, participants expected the digital assistant to understand and process complex requests mitigated with hedging words and expressions, and peppered with vague language and deictic references requiring shared contextual information and mutual understanding. Findings are presented in six themes which emerged during the analysis - formulating responses; turn-taking; back-channelling, fillers and hesitation; vague language; mitigating requests and politeness and praise. The results can be used to inform the design of future in-vehicle natural language systems, in particular to help manage the tension between designing for an engaging dialogue (important for technology acceptance) and designing for an effective dialogue (important to minimise distraction in a driving context).
In a longitudinal study, 49 drivers undertook a commutestyle journey, with part of the route supporting level-3 automation, over five consecutive days. Bespoke HMIs were provided to keep drivers in-the-loop during automation, and help them regain situational-awareness (SA) during handovers, in a 2×2 between-subjects design. Drivers demonstrated high levels of trust from the outset, delegating control to the vehicle (when available) and directing attention to their own activities/devices. Ratings of trust and technology acceptance increased during the weekeven following an unexpected, emergency handover on day fourwith the highest ratings recorded on day five. High levels of lateral instability were observed immediately following takeovers, although improvements were noted during the week and following the provision of SA-enhancing hand-over advice. Results demonstrate benefits associated with novel HMI designs to keep drivers in-the-loop and improve takeover performance, as well as the necessity of multiple exposures during the evaluation of future, immersive technologies.
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