Autonomous driving at scale is approaching, yet human drivers are reluctant to relinquish control over their safety to a machine. Autonomous vehicle designers are thus challenged to mitigate user concern and promote trust—as well as to ensure safety under the new driving paradigm. If autonomous cars are to become commonplace, the car-to-driver interface must be designed around the user—driver and passenger. This research adopts a human-centered approach to interface design, studying the emotional responses and preferences of drivers in autonomous and semi-autonomous driving situations. The dissertation posits that the complex, rapid-response driving context calls for the car to provide advance, feed-forward information rather than just traditional feedback. This approach was tested in a set of four experiments: two involved semi-autonomous driving in a simulator environment using voice alerts, and two involved more fully autonomous driving in an actual car on public roadways using a visual display as the messaging medium. In all cases, drivers strongly preferred being kept in the information loop. Advance alerts, whether vocal or visual, alleviated anxiety, and increased the driver's alertness, sense of control, and trust in the technology. Messaging should be succinct; too much information overwhelmed drivers, who could not process multiple messages in the rapid-response driving context. Drivers considered the reasoning behind the car's autonomous action (e.g., "Obstacle ahead!") more salient than mere announcement of the car's action (e.g., "Car is braking"). Designers must beware that consumer preferences do not dictate the best (or safest) performance; study results anticipate potential tradeoffs between market appeal and safety. Beyond empirical results for specific message models, this work developed simulator and field research platforms that can be adapted for future investigations. The research culminates in core guidelines for designing an autonomous vehicle interface that satisfies driver needs.

Emotions play a central role in the human's ability to understand the world as well as in affecting consumers' perception of products, which further determine purchase intention and consumers' decisions to trust a product. Creating a specific emotional connection between consumers and products can enrich user experience, enhance product adoption, and increase user-to-product trust. Therefore, it is important for engineers and designers to understand how consumers perceive products regarding emotional connections and whether or not emotive stimuli affect consumers' perception and trust level of products. Insights in understanding emotional connections and effects of emotions on trust will help designers to effectively bond consumers and products and will also enable designers in calibrating user-to-product trust to a healthy level. To study the emotional connections that relate to use-to-product trust, the work presented in this dissertation employed a collage tool and the psychological priming technique in two different ways: first, the collage tool was used to examine how consumers evaluate products concerning emotional connections; second, the priming technique was applied to evoke designated emotions and stimulate a desirable design mindset. Currently, industrial designers rely on artistic intuition to evoke specific emotions in product aesthetics. A more systematic method is needed to measure emotional responses and to understand the association between product features and emotions. Study 1 in Chapter 2 proposed a two-axis collage tool to measure emotional connections in a visual and interactive way. Using the collage tool, the study participants evaluated a variety of wearable products and determined whether or not they perceived the wearables as comfortable, delightful or useful. In addition to determining purchase intention, emotions can potentially influence users' decisions to trust by affecting their mental state and perception of products. Derived from theories of interpersonal trust, trusting products involves both cognitive and affective processes—users assess a product's ability using analytic thought processes, and also weigh affective factors such as emotional investments, concerns for others and the beliefs of reciprocity of sentiment. Study 2 in Chapter 3 investigates the affective process of forming trust in interactive products, so that designers can manipulate users' trust to prevent misuse and disuse. The study investigated the affective process of trust formation of the Amazon Echo, an autonomous voice-activated assistant, by priming study participants with emotive images prior to interacting with the Echo. As priming successfully changed user-to-product trust by influencing users' mental state, the priming technique can also be applied to influence designers' mindsets. Study 3 in Chapter 4 applied priming to alter designers' mindsets prior to conceptual design exercises and investigated whether or not priming method improved ideation outcomes in terms of relevance to the sustainability pillars and ideas' intrinsic quality, as judged by experts, and also whether or not it caused designers to decrease the favoring of one's own ideas compared to the ideas of others during idea evaluation. This dissertation demonstrates the effect of emotions on users' perception of products and also the effect of manipulating mental state or mindset on users' decision and designers' capability. The results underscore the importance of understanding the mental model and the subconscious mindset of both users and designers in design processes. Insights from this research will help build academic theory and design guidance about how to ensure future technology to be socially desirable, collaborative and sustainable