Lack of trust can induce drivers to not use all the functionalities provided by an automated vehicle while excessive trust can create safety issues, leading drivers to use the system in ways that were not intended by the designers. To understand trust, it is necessary to consider its multilayered nature, bringing together dispositional, situational and learned trust. It is also necessary to understand that trust is dynamic, changing over different time scales, ranging from seconds to years. However, some aspects of trust have received more attention than others. For instance, few studies have investigated how trust changes with experience, attempted to identify appropriate levels of trust, or discussed how to achieve them. Studies on how to measure trust are also rare. These are the kind of issues we will address in this Research Topic.
The aim of this Research Topic is to bring together interdisciplinary Human Factors research on trust in automated driving technology – from features already present in commercially available vehicles, through to the new technologies required for SAE Level 5 systems. This Research Topic will prioritize original research and literature reviews that expand on what is already known and tackle aspects of trust that have not been adequately addressed in the literature. For example, research on methods to measure trust in real-life situations, longitudinal studies of trust over extended periods of time, studies of the key factors affecting trust and vehicle design, and policy solutions addressing critical issues. Individual articles may focus on specific trust layers (e.g. dispositional, situational, learned trust), different categories of road users (e.g. drivers, pedestrians), in vehicles with levels of automation ranging from SAE Level 2 to SAE level 5. Novel hypothesis and methodological approaches are particularly welcome. Overall, the Research Topic should provide valuable input for the development of future applications, better policies, better human-machine interfaces, and safer roads.
We are interested in original on-road and simulator studies, and research reviews addressing key issues of trust in automated vehicles. Possible topics include, but are not limited to:
- What is trust in automated vehicles. How can we define it and how does it differ from interpersonal trust?
- How can trust be reliably (and continuously) measured?
- How does trust evolve over time?
- How do situational (e.g. road type, weather) and dispositional (e.g. personality, age) factors affect trust in automated vehicles?
- Trust calibration and its impact on safety and system usage.
- Vehicle design features (e.g. HMIs) impacting trust.
- Other measures impacting trust (e.g. road design, signage).
- Other applications and aspects of trust in automated vehicles not mentioned above.
- Novel concepts, methods and hypothesis related to trust in automated vehicles.
Guest editors Dr. Hergeth and Dr. Forster are currently employed by the BMW Group. The remaining editors have no conflicts of interest to declare.
Lack of trust can induce drivers to not use all the functionalities provided by an automated vehicle while excessive trust can create safety issues, leading drivers to use the system in ways that were not intended by the designers. To understand trust, it is necessary to consider its multilayered nature, bringing together dispositional, situational and learned trust. It is also necessary to understand that trust is dynamic, changing over different time scales, ranging from seconds to years. However, some aspects of trust have received more attention than others. For instance, few studies have investigated how trust changes with experience, attempted to identify appropriate levels of trust, or discussed how to achieve them. Studies on how to measure trust are also rare. These are the kind of issues we will address in this Research Topic.
The aim of this Research Topic is to bring together interdisciplinary Human Factors research on trust in automated driving technology – from features already present in commercially available vehicles, through to the new technologies required for SAE Level 5 systems. This Research Topic will prioritize original research and literature reviews that expand on what is already known and tackle aspects of trust that have not been adequately addressed in the literature. For example, research on methods to measure trust in real-life situations, longitudinal studies of trust over extended periods of time, studies of the key factors affecting trust and vehicle design, and policy solutions addressing critical issues. Individual articles may focus on specific trust layers (e.g. dispositional, situational, learned trust), different categories of road users (e.g. drivers, pedestrians), in vehicles with levels of automation ranging from SAE Level 2 to SAE level 5. Novel hypothesis and methodological approaches are particularly welcome. Overall, the Research Topic should provide valuable input for the development of future applications, better policies, better human-machine interfaces, and safer roads.
We are interested in original on-road and simulator studies, and research reviews addressing key issues of trust in automated vehicles. Possible topics include, but are not limited to:
- What is trust in automated vehicles. How can we define it and how does it differ from interpersonal trust?
- How can trust be reliably (and continuously) measured?
- How does trust evolve over time?
- How do situational (e.g. road type, weather) and dispositional (e.g. personality, age) factors affect trust in automated vehicles?
- Trust calibration and its impact on safety and system usage.
- Vehicle design features (e.g. HMIs) impacting trust.
- Other measures impacting trust (e.g. road design, signage).
- Other applications and aspects of trust in automated vehicles not mentioned above.
- Novel concepts, methods and hypothesis related to trust in automated vehicles.
Guest editors Dr. Hergeth and Dr. Forster are currently employed by the BMW Group. The remaining editors have no conflicts of interest to declare.
