With highly automated vehicles (HAVs), the human role shifts from active driver to mostly passive passenger, which has an impact on the perceived comfort while being driven. A number of factors need to be taken into account when designing an automated driving style (ADS) with the aim to minimize human discomfort. In this paper, the authors build on seven empirical studies to determine first, if a generally comfortable ADS exists and second, whether such an ADS should be designed depending on situational driving dynamics or individual user characteristics such as users’ manual driving styles. The results give an overview of the ADS- and user-related factors causing human discomfort in automated driving and provide potential strategies to overcome potential discomfort. Drawing on the data, upcoming challenges in the field of human discomfort in HAVs for both research and practice are presented.

Today’s research on fenceless human–robot collaboration (HRC) is challenged by a relatively slow development of safety features. Simultaneously, design recommendations for HRC are requested by the industry. To simulate HRC scenarios in advance, virtual reality (VR) technology can be utilized and ensure safety. VR also allows researchers to study the effects of safety-restricted features like close distance during movements and events of robotic malfunctions. In this paper, we present a VR experiment with 40 participants collaborating with a heavy-load robot and compare the results to a similar real-world experiment to study transferability and validity. The participant’s proximity to the robot, interaction level, and occurring system failures were varied. State anxiety, trust, and intention to use were used as dependent variables, and valence and arousal values were assessed over time. Overall, state anxiety was low and trust and intention to use were high. Only simulated failures significantly increased state anxiety, reduced trust, and resulted in reduced valence and increased arousal. In comparison with the real-world experiment, non-significant differences in all dependent variables and similar progression of valence and arousal were found during scenarios without system failures. Therefore, the suitability of applying VR in HRC research to study safety-restricted features can be supported; however, further research should examine transferability for high-intensity emotional experiences.

In an increasingly urban and sustainable transportation-focused world, cycling emerges as a key environmentally friendly and health-promoting mode of travel. This paper addresses the gap in understanding cyclists' subjective safety, particularly in relation to bicycle streets in Germany. Utilizing a multimodal approach, two studies were conducted: an online questionnaire (Study I) and a Virtual Reality (VR) evaluation (Study II), focusing on the Reichenhainer Straße in Chemnitz. Study I involved N = 182 participants who regularly used the bicycle street. The questionnaire covered various aspects including mobility behavior, cycling experience, and subjective safety, using a 6-point Likert scale. Infrastructure characteristics were represented through images. Results showed that participants generally felt safe on the bicycle street, with key factors being the lane width and restrictions on motorized traffic. Study II, a pioneering effort in using VR and stereoscopic 360° images for evaluating cycling infrastructure safety, involved N = 32 participants. It provided a realistic evaluation of infrastructure elements and their impact on perceived safety. The study revealed significant differences in safety ratings based on the presence of cars and cyclists' experience levels. The use of VR allowed for a focused examination of infrastructure characteristics and their perceived safety, highlighting potential areas for improvement. Both studies demonstrated consistent results, underscoring the subjective safety of the Reichenhainer Straße, which was perceived as safer than the average bike-accessible infrastructure in Chemnitz. The VR method proved effective for detailed evaluation of subjective safety, independent of participants' familiarity with the specific infrastructure. This approach offers a structured, controlled, and resource-efficient way to evaluate cycling infrastructure under laboratory conditions. In conclusion, the findings align with existing literature and emphasize the importance of lane width and reduced motorized traffic for cyclists' safety. The innovative VR method, while still developing, offers promising implications for future citizen participation initiatives and infrastructure planning projects, enabling efficient post-completion evaluations of subjective safety. Such practices are rare in German planning offices, highlighting the paper's contribution to enhancing urban cycling infrastructure planning and safety assessment.

Handing over objects is a collaborative task that requires participants to synchronize their actions in terms of space and time, as well as their adherence to social standards. If one participant is a social robot and the other a visually impaired human, actions should favorably be coordinated by voice. User requirements for such a Voice-User Interface (VUI), as well as its required structure and content, are unknown so far. In our study, we applied the user-centered design process to develop a VUI for visually impaired humans and humans with full sight. Iterative development was conducted with interviews, workshops, and user tests to derive VUI requirements, dialog structure, and content. A final VUI prototype was evaluated in a standardized experiment with 60 subjects who were visually impaired or fully sighted. Results show that the VUI enabled all subjects to successfully receive objects with an error rate of only 1.8%. Likeability and accuracy were evaluated best, while habitability and speed of interaction were shown to need improvement. Qualitative feedback supported and detailed results, e.g., how to shorten some dialogs. To conclude, we recommend that inclusive VUI design for social robots should give precise information for handover processes and pay attention to social manners.

The rapidly growing research on the accessibility of digital technologies has focused on blind or visually impaired (BVI) users. However, the field of human–robot interaction has largely neglected the needs of BVI users despite the increasing integration of assistive robots into daily life and their potential benefits for our aging societies. One basic robotic capability is object handover. Robots assisting BVI users should be able to coordinate handovers without eye contact. This study gathered insights on the usability of human–robot handovers, including 20 BVI and 20 sighted participants. In a standardized experiment with a mixed design, a handover robot prototype equipped with a voice user interface and haptic feedback was evaluated. The robot handed over everyday objects (i) by placing them on a table and (ii) by allowing for midair grasping. The usability target was met, and all user groups reported a positive user experience. In total, 97.3% of all handovers were successful. The qualitative feedback showed an appreciation for the clear communication of the robot’s actions and the handover reliability. However, the duration of the handover was seen as a critical issue. According to all subjective criteria, the BVI participants showed higher variances compared to the sighted participants. Design recommendations for improving robotic handovers equally supporting both user groups are given.