User trust here and now but not necessarily there and then - A Design Perspective on Appropriate Trust in Automated Vehicles (AVs)
Doctoral thesis, 2023

Automation may carry out functions previously conducted only by humans. In the past, interaction with automation was primarily designed for, and used by, users with special training (pilots in aviation or operators in the process industry for example) but since automation has developed and matured, it has also become more available to users who have no additional training on automation such as users of automated vehicles (AVs). However, before we can reap the benefits of AV use, users must first trust the vehicles. According to earlier studies on trust in automation (TiA), user trust is a precondition for the use of automated systems not only because it is essential to user acceptance, but also because it is a prerequisite for a good user experience. Furthermore, that user trust is appropriate in relation to the actual performance of the AV, that is, user trust is calibrated to the capabilities and limitations of the AV. Otherwise, it may lead to misuse or disuse of the AV.
     The issue of how to design for appropriate user trust was approached from a user-centred design perspective based on earlier TiA theories and was addressed in four user studies using mixed-method research designs. The four studies involved three types of AVs; an automated car, an automated public transport bus as well as an automated delivery bot for last-mile deliveries (LMD) of parcels. The users’ ranged from ordinary car drivers, bus drivers, public transport commuters and logistic personnel.
     The findings show that user trust in the AVs was primarily affected by information relating to the performance of the AV. That is factors such as, how predictable, reliable and capable the AV was perceived to be conducting for instance a task, as well as how appropriate the behaviour of the AV was perceived to be for conducting the task and whether or not the user understood why the AV behaved as it did when conducting the task. Secondly, it was also found that contextual aspects influenced user trust in AVs. This primarily related to the users’ perception of risk for oneself and others as well as perceptions of task difficulty. That is, user trust was affected by the perception of risk for oneself but also by the possible risks the AV could impose on other e.g. road users. The perception of task difficulty influenced user trust in situations when a task was perceived as (too) easy, the user could not judge the trustworthiness of the AV or when the AV increased the task difficulty for the user thus adding to negative outcomes. Therefore, AV-related trust factors and contextual aspects are important to consider when designing for appropriate user trust in different types of AVs operating in different domains.
     However, from a more in-depth cross-study analysis and consequent synthesis it was found that when designing for appropriate user trust the earlier mentioned factors and aspects should be considered but should not be the focus. They are effects, that is the user’s interpretation of information originating from the behaviour of the AV in a particular context which in turn are the consequence of the following design variables: (I) The Who i.e. the AV, (II) What the AV does, (III) by What Means the AV does something, (IV) When the AV does something, (V) Why the AV does something and(VI) Where the AV does something, as well as the interplay between them. Furthermore, it was found that user trust is affected by the interdependency between (II) What the AV does and (VI) Where the AV does something; this was always assessed together by the user in turn affecting user trust. From these findings a tentative Framework of Trust Analysis & Design was developed. The framework can be used as a ‘tool-for-thought’ and accounts for the activity conducted by the AV, the context as well as their interdependence that ultimately affect user trust.

Automated Vehicles (AV)

Design Variables, Trust Framework

Appropriate User Trust

User-Centred Design Perspective

Contextual Aspects

Trust Factors

Information

Virtual Development Laboratory (VDL)
Opponent: Prof. John D. Lee; University of Wisconsin Madison; USA

Author

Fredrick Ekman

Chalmers, Industrial and Materials Science, Design & Human Factors

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

Journal article

Trust in what? Exploring the interdependency between an automated vehicle’s driving style and traffic situations

Transportation Research Part F: Traffic Psychology and Behaviour,; Vol. 76(2021)p. 59-71

Journal article

Aspects Influencing Users' Trust in an Automated Delivery Bot: A Pilot Study

ADAS at Work: assessing professional bus drivers' experience and acceptance of a narrow navigation system.

Cognition, Technology and Work,; Vol. 24(2022)p. 625-639

Journal article

Automation as an enabler: Passengers’ experience of travelling with a full-length automated bus and expectations of future public transport system.

Automated Vehicles (AVs) such as automated cars, public transport (PT) busses and delivery bots for last-mile deliveries (LMD) may increase traffic safety, improve user comfort and reduce personnel costs. However, before we can reap the benefits of AV use, users must first trust the vehicles no matter operative domain (OD). Not only because trust is essential to user acceptance, but also because it is a prerequisite for a good user experience. However, even though user trust is important for use, acceptance and good user experience it is even more important that user trust in AVs is appropriate to the actual performance of the system. So to reap the benefits, users must fully understand the capabilities and limitations of the AV.
 
The work presented in this thesis explores what factors affects user trust when the user is using different AVs in different ODs: (i) automated car for private transport in the regular traffic system, (ii) automated bus for public transport in the regular traffic system, and (iii) automated delivery bot for last-mile deliveries (LMD) of parcels within a logistic system. In addition, the work presents what, from a design perspective, is important to consider when designing for appropriate user trust.
 
The findings show that user trust was, regardless of AV type or OD, primarily affected by how well the AV performed when conducting tasks, such as negotiating a traffic situation, by how appropriate the behaviour of the AV was perceived to be when conducting a task and whether or not the user understood why the AV behaved as it does. Furthermore, it was found that user trust was influenced by the contextual aspects in terms of potential risks and how difficult the tasks were perceived to be.
 
However, the most important finding was that user trust was always affected by the interdependency between what the AV did and where. For example, users trusted the AV for conducting a task in one context, such as negotiating a specific traffic situation in an industrial area but not for the activity of negotiating traffic situations in a city-centre.
 
From these findings a tentative Framework of Trust Analysis & Design was developed. The framework describes what is important to consider when designing for appropriate trust; that user trust is affected by information created in the interplay between what the AV does (a task), why the AV behaves as it does (when conducting the task) and where (in which context the task is conducted) and that trust in an AV may differ depending on what the AV should do and in what context.

Designing for appropriate trust between driver and AV - TRUST

Chalmers, 2018-01-01 -- 2021-06-30.

Subject Categories

Mechanical Engineering

Computer and Information Science

Psychology

Human Computer Interaction

Areas of Advance

Information and Communication Technology

Transport

ISBN

978-91-7905-798-5

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5264

Publisher

Chalmers

Virtual Development Laboratory (VDL)

Opponent: Prof. John D. Lee; University of Wisconsin Madison; USA

More information

Latest update

1/30/2023