Trusting autonomous vehicles: an interdisciplinary approach

Kaspar Raats, Vaike Fors, Sarah Pink

Research output: Contribution to journalArticleResearchpeer-review

39 Citations (Scopus)


The theoretical concept of trust has been identified as highly important to the successful design of intelligent technologies such as autonomous vehicles (AVs). In human-centred transport research this has resulted in a focus on trust in the technical design of future AVs and has raised the question of how the conditions that form trust change as technologies become more intelligent. In this article we discuss the first stage of an interdisciplinary project that brought together ethnographic and experimental user studies into trust in intelligent cars. This stage focused on the development of an interdisciplinary methodological framework for the user studies, through a review of 258 empirical HCI research articles on trust in automation and AVs. The review investigated the following research questions: a) what are the key themes in HCI methodologies used to research trust in automation and AVs; b) how do they account for trust in AVs as part of wider contexts; and c) how can these methodologies be developed to include more than momentary and individual human-machine interactions. We found that while theoretical understandings of trust in automated technologies acknowledge the relevance of the wider context in which the interaction occurs, existing methodologies predominantly involve experimental studies in simulated environments with a focus on reliance related aspects of trust. We identified that ethnographic user studies can potentially contribute to new connections between theoretical understandings and conventional experimental methods. Therefore, we propose a framework for an interdisciplinary approach that combines experimental and ethnographic methodologies to investigate trust in AVs.

Original languageEnglish
Article number100201
JournalTransportation Research Interdisciplinary Perspectives
Publication statusPublished - Sept 2020


  • Autonomous vehicles
  • Emerging technologies
  • Human-computer interaction trust research
  • Intelligent automation

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