The absence of a human driver creates novel challenges for fully automated public transport. Passengers are likely to have different expectations, needs, or even fears when traveling without a driver in potentially dangerous situations. We present the results from two field studies in which we explored incident management in a driverless shuttle bus. We explored participant’s behavior and willingness to assist in solving problems in a variety of scenarios where the bus suddenly stops for technical reasons or a hypothesized situation of harassment. In a follow-up study, we focused on auditory remote assistance and investigated problem solving through the passengers. We found that diffusion of responsibility is an existent barrier, when passengers are involved in the resolving of potentially dangerous situations. It can be overcome, when incident-relevant instructions are designed explicitly, briefly, timely, distinguishable from regular on-trip information, and address auditory and visual sensory channels alike.

Automated shuttles are already seeing deployment in many places across the world and have the potential to transform public mobility to be safer and more accessible. During the current transition phase from fully manual vehicles toward higher degrees of automation and resulting mixed traffic, there is a heightened need for additional communication or external indicators to comprehend automated vehicle actions for other road users. In this work, we present and discuss the results from seven studies (three preparatory and four main studies) conducted in three European countries aimed at investigating and providing a variety of such external communication solutions to facilitate the exchange of information between automated shuttles and other motorized and non-motorized road users.

The energy transition requires increased end-user flexibility in consumption as a response to the more volatile production patterns of renewable resources. Automated demand-side management solutions can provide support in achieving this but struggle with trust and acceptance issues from end-users. This paper contributes insights into how communicating trustworthiness can be achieved through careful and context-aware interaction design in such systems. Core interface features such as feedback, automation transparency, control options, benefit information, and actionable information were identified and fifteen case studies from six countries were analysed with regard to provided interaction features, automation level, and end-user experiences. The results provide insights into the form and frequency of these features used at different automation levels and their varying role in trust and acceptance building. Based on our results, we recommend particular attention to providing actionable information and actively reaching out to users at a low automation level, to provision and communication of control at a medium automation level, and to providing transparency at a high automation level in order to promote trust successfully, while benefit information is central for a “social license to automate” independently of the automation level.

Despite the growing availability of data, simulation technologies, and predictive analytics, it is not yet clear whether and under which conditions users will trust Decision Support Systems (DSS). DSS are designed to support users in making more informed decisions in specialized tasks through more accurate predictions and recommendations. This mixed-methods user study contributes to the research on trust calibration by analyzing the potential effects of integrated reliability indication in DSS user interfaces for process management in first-time usage situations characterized by uncertainty. Ten experts specialized in digital tools for construction were asked to test and assess two versions of a DSS in a renovation project scenario. We found that while users stated that they need full access to all information to make their own decisions, reliability indication in DSS tends to make users more willing to make preliminary decisions, with users adapting their confidence and reliance to the indicated reliability. Reliability indication in DSS also increases subjective usefulness and system reliability. Based on these findings, it is recommended that for the design of reliability indication practitioners consider displaying a combination of reliability information at several granularity levels in DSS user interfaces, including visualizations, such as a traffic light system, and to also provide explanations for the reliability information. Further research directions towards achieving trustworthy decision support in complex environments are proposed.

In conditionally automated driving, assertive takeover requests (TORs) have been found to elicit faster responses in the transition from automated to manual control. However, despite this apparent benefit, concerns have been raised that assertive signals can stress the drivers, resulting in worse takeover quality and subsequent driving performance. To investigate the phenomenon, we conducted a driving simulator study exploring the effects of assertive and non-assertive TOR signals. In a series of tasks where the drivers were required to take over control of the vehicle to manually maneuver a critical situation, immediate and sustained measures of driving performance, stress, and subjective perceptions were compared. Consistent with previous research, the assertive signal led to shorter reaction times and stronger braking. However, no other immediate or delayed differences in the measures were observed. These findings suggest that assertive TOR signals might be a preferable design option, however, the phenomenon should be further explored.