Driving an autonomic vehicle is terrifying to a lot of people, especially for those without knowledge and experience of this type of technology. Today, several companies within the automotive industry are working towards autonomous driving. Tesla, Waymo and Uber are three companies who already has the technology to drive autonomously. It is the future and this technology changes the driver’s role. The driver is now not only expected to take control but also to give control to the system. As mentioned above, this change is not welcomed by everyone due to fear. This is a challenge for the automotive industry and the question is therefore how the industry can make people trust the vehicles of the feature?
This thesis is focused on how one can design appropriate trust through voice interaction in autonomous cars, using the learning intelligent vehicle (LIV) which is a concept research platform by Veoneer. The research in this thesis includes a user study including an observation study that was conducted on a local fair in Vårgårda with focus on a UX perspective with possible future end users. Since there are restricted methods of evaluation methods on voice interaction, the author uses the Gricean Maxims to evaluate the existing voice interaction of LIV. By using user studies and the Gricean Maxims, the author argues that these methods can be used to identify trust characteristics and create appropriate trust before the actual launch of the vehicle/system. For example, when exhibit the autonomous vehicle to the public.