Designing for Appropriate Trust in Automated Vehicles
Licentiate thesis, 2020
This thesis presents two mixed-method studies (Study I and II). The first study considers what factors affect users trust in the AV and is primarily based on a literature review as well as a complementary user study. The second study, a user study, is built upon Study I and uses a Wizard of Oz (WOz) approach with the purpose to understand how the behaviour of an AV affects users trust in a simulated but realistic context, including seven day-to-day traffic situations.
The results show that trust is primarily affected by information from and about the AV. Furthermore, results also show that trust in AVs have primarily four different phases, before the user’s first physical interaction with the AV (i), during usage and whilst learning how the AV performs (ii), after the user has learned how the AV performs in a specific context (iii) and after the user has learned how the AV performs in a specific context but that context changes (iv). It was also found that driving behaviour affects the user’s trust in the AV during usage and whilst learning how the AV performs. This was primarily due to how well the driving behaviour communicated intentions for the users’ to be able to predict upcoming AV actions. The users’ were also affected by the perceived benevolence of the AV, that is how respectful the driving behaviour was interpreted by the user. Finally, the results also showed that the user’s trust in the AV also is affected by aspects relating to different traffic situations such as perceived task difficulty, perceived risk for oneself (and others) and how well the AV conformed to the user’s expectations. Thus, it is not only how the AV performs but rather how the AV performs in relation to different traffic situations.
Finally, since design research not only considers how things are, but also how things ought to be, a tentative explanatory and prescriptive model was developed based on the results presented above. The model of trust information exchange and gestalt explains how information affecting user trust, travels from a trust information sender to a trust information receiver and highlights the important aspects for developers to consider designing for appropriate trust in AVs, such as the design space and related variables. The design variables are a) the message (the type and amount of information), b) the artefact (the AV, including communication channels and properties) and c) the information gestalt, which is based on the combination of signals communicated from the properties (and communication channels). In this case, the gestalt is what the user ultimately perceives; the combined result of all signals. Therefore, developers need to consider not only how individual signals are perceived and interpreted, but also how different signals are perceived and interpreted together, as a whole, an information gestalt.
trust phases, driving behaviour, explanatory and prescriptive model, information gestalt.
automated vehicles (AVs)
mixed method research
Chalmers, Industrial and Materials Science, Design and Human Factors
Creating Appropriate Trust in Automated Vehicle Systems: A Framework for HMI Design
IEEE Transactions on Human-Machine Systems,; Vol. 48(2018)p. 95-101
Exploring automated vehicle driving styles as a source of trust information
Transportation Research Part F: Traffic Psychology and Behaviour,; Vol. 65(2019)p. 268-279
Fredrick Ekman, Mikael Johansson, MariAnne Karlsson, Helena Strömberg and Lars-Ola Bligård - Trust in What? Exploring the Interdependency between an Automated Vehicle’s Driving Style and Traffic Situations
Designing for appropriate trust between driver and AV - TRUST
Chalmers, 2018-01-01 -- 2021-06-30.
Areas of Advance
Human Computer Interaction
Chalmers University of Technology
Opponent: Jonas Andersson PhD, Senior researcher at RISE, Sweden