A Thematic Analysis on Trust-Building Mechanisms in Autonomous Vehicles

Abstract

Autonomous vehicles (AVs) have a wide range of potential advantages, and they open up new transportation options. However, these advantages can only be realized if the general public accepts AVs. One of the requirements preceding acceptance is trust in such an autonomous technology, which is critical to its success. But currently, a significant part of the population does not seem to trust AVs. To address this issue, research is trying to approach the problem from different perspectives. First, from a psychological perspective, which specifically examines human factors, and second, from a technical perspective, which looks at technical solutions. This work attempts to combine and report from both perspectives. A literature search was conducted for this purpose, which led to 55 relevant scientific papers. Based on the literature base, a Thematic Analysis (TA) was conducted to find trust influencing themes and sub-themes. Altogether, 24 trust-influential sub-themes (characteristics) were identified, which were classified into 6 distinct themes: (1) Information Exchange, (2) User Perception and Comprehension, (3) Perceived Intelligence - from a technological perspective, and (4) Trust in the Manufacturer, (5) Trust in the Technology, and (6) Trust in the Legislative - from a psychological perspective. Based on our results, we argue that trust in AVs should not be seen as a binary problem, and cannot be significantly increased by covering single, selected characteristics alone. Our results show that trust in AVs can even decrease when individual characteristics are unduly addressed. As a result, if trust in AVs is to be increased, specific characteristics’ interdependencies must be evaluated and treated accordingly.