What should an intelligent in-vehicle assistant (IVA) look like, and how should it behave to truly enhance the in-car experience? We present a large-scale video-based online experiment (n = 1238) exploring how IVA design factors influence user perceptions. Participants evaluated two scenarios (adjusting temperature, adjusting seat position) across 32 conditions varying in autonomy (user-initiated, system-initiated, autonomous with explanation, autonom- ous without explanation), embodiment (abstract virtual agent, humanlike virtual agent, abstract robot, humanoid robot), and conversational style (formal, informal). Contrary to prevailing academic trends, our findings reveal a clear preference against robotic embodiments and high levels of autonomy, sometimes even when explainable. Instead, participants favored proactivity with lower system autonomy and less anthropomorphic designs. We discuss how these insights challenge current design assumptions and offer concrete guidelines for shaping IVAs that align with driver expectations and comfort. This work contributes an empirically grounded understanding of IVA appearance, behavior, and communication style to inform future human-centered automotive interaction design.

Explanations are central to improving transparency, trust, and user satisfaction in recommender systems (RS), yet it remains unclear how different explanation formats (visual vs. textual) are suited to users with different personal characteristics (PCs). To this end, we report a within-subject user study (n=54) comparing visual and textual explanations and examine how explanation format and PCs jointly influence perceived control, transparency, trust, and satisfaction in an educational recommender system (ERS). Using robust mixed-effects models, we analyze the moderating effects of a wide range of PCs, including Big Five traits, need for cognition, decision making style, visualization familiarity, and technical expertise. Our results show that a well-designed visual, simple, interactive, selective, easy to understand visualization that clearly and intuitively communicates how user preferences are linked to recommendations, fosters perceived control, transparency, appropriate trust, and satisfaction in the ERS for most users, independent of their PCs. Moreover, we derive a set of guidelines to support the effective design of explanations in ERSs.

The increasing deployment of delivery robots has highlighted both opportunities and challenges, including intentional and unintentional impediments to these robots. This study explores the design space of robot behavior to respond to such situations while considering the social group characteristics of the human interactants from the perspective of a bystander. In focus groups (n = 13), we identified human personas who (un)intentionally impede the tasks of delivery robots and collaboratively designed potentially suitable robot responses, resulting in the identification of seven human personas and five robot personas. The suitability of robot responses to human personas was subsequently evaluated in a within-between-subject online survey (n = 49), which also examined the influence of gendered robot voice (male vs. female; between-subject factor). The findings reveal a clear preference for passive and polite robot responses over assertive robot responses, with no significant differences in perception between male and female-voiced robots. This study provides insights for designers seeking to create effective and socially aware delivery robots capable of managing obstructive encounters.

This study addresses how anthropomorphic features shape users' social perception and trust towards service robots and whether anthropomorphic characteristics influence the way people jointly navigate with them facing several obstacles in a course. Therefore, an experimental study was conducted where two communication and appearance designs (humanlike vs. machinelike) were examined for a service robot that provides transportation of goods by semi-automated following. The results of the study indicate that the humanlike robot design is rated more competent, warmer, less discomforting, and is generally preferred. Furthermore, participants jointly navigating with the humanlike designed robot walked around obstacles significantly more often indicating a more considerate navigation behavior and better remembering of system limits; both probably evoked by the humanlike design characteristics. In sum, the results of this study provide intriguing implications on how to target HRI for the service robot examined to enhance pleasant and error-free interaction.

When social robots are joining human teams it is relevant to not only study the social dynamics within these human-robot mixed groups but also to explore whether outsiders perceive them as groups. Perceiving higher or lower groupness of mixed groups potentially influences which expectations individuals have towards the group, its human and importantly its robot members. We examined how much outsiders perceive differently composed human-robot groups as a group. In a between-subjects video-based online study, participants rated videos of group interactions with diverse group compositions (i.e., 1 robot with 3 humans, 2 robots with 2 humans, and 3 robots with 1 human) whose members either did or did not wear a visual group token (i.e., the same wristband) regarding the perceived groupness. Group composition and visual token influenced perceived groupness with a group of 1 human and 3 robots being less perceived as a group. Visual tokens enhanced group perceptions. This research contributes to our comprehension of how people perceive human-robot groups.

Prevention of abuse of autonomous robots is one of the major challenges in getting robots out”in the wild The involvement of observing pedestrians of an abusive situation might be a key factor to stop abuse. We investigated how a delivery robot’s different reactions to abuse affect an observer’s situational empathy and affect towards the robot. In two studies, a total of 364 participants watched short videos of a delivery robot being kicked by an “abuser” and observed one of four different pre-tested robot reactions towards abuse: sad face, neutral face, white screen, and black screen. Concerning negative affect and situational empathy towards the robot and the abuser, significant differences were found between screen on conditions (sad, neutral, white) and the screen off condition (black screen). No differences were found between the different screen on conditions. Especially, negative affect, ascribed warmth to the robot, and empathetic concern significantly predicted situational empathy. Humans seem to empathize most with a delivery robot indicating “being on” (white screen or facial expression) while the emotional facial reaction had no effects. Thus, autonomous robots should always show signs of being turned on when operating autonomously on the streets in order to raise empathy and prevent abuse.

Favorable assessments of social robots are addressed in several research and development attempts because positive attitudes and intentions towards technology are regarded as a necessary prerequisite for usage. To predict a favorable evaluation, it is inevitable to understand the appraisal process and determine crucial variables that affect the evaluative and behavioral consequences of HRI. Robotic morphology has been identified as one of these variables. In the present work, we expand previous work by demonstrating that capability attributions associated with robots’ morphological features explain variations in evaluations. Based on two large picture-based online studies (Study 1, n = 673; Study 2, n = 586) we show that robots with similar morphological features (e.g., robots with arms and grippers) can be clustered along their assigned capabilities, and that these capabilities (e.g., to manipulate objects) explain evaluations of the robots in terms of acceptance and social attributes (i.e., warmth, competence, and discomfort). We discuss whether these initial assessments are relevant to live interactions and how our results can inform robot design.

In this work, we provide an argument and first empirical insights that existing technology acceptance models fall short when it comes to explaining spontaneous, unplanned and unsolicited encounters between humans and delivery robots on the street. Since technology acceptance models have been defined by the technology's perceived ease of use, perceived usefulness and behavioural intention to use, they are not well suited to explain acceptance in situations in which humans meet robots without any prior intention to use. Nevertheless, acceptance of delivery robots might be a driving force for safe navigation. Thus, the concept of acceptance should not be limited to its current focus on (planned) usage. In consequence, we i) expand the understanding of technology acceptance, ii) propose the concept of Existence Acceptance for autonomous systems, and iii) explore a new model for acceptance in an online study (n = 185). Theoretical considerations hint towards the relevance of existence acceptance models for autonomous systems.

This paper addresses how robots should communicate with humans so that the interaction is successful and satisfying for the user. Specifically, within the present study, nine different communication strategies were examined for a service robot that provides transportation of goods by semi-automated following. The communication style (humanlike friendly, humanlike professional, machinelike) and modality (auditive male, auditive female, visual) of communication was varied and their influence on system evaluation regarding competence, warmth, discomfort, embodiment and preferences were investigated in an online study. The results of the study indicate that a humanlike communication is rated more competent, warmer, less discomforting, and is generally preferred. With regard to gender, no clear preferences or differences in evaluation were found. In terms of modality, a combination of auditive and visual interaction was favored. It should be noted that the data were collected online and verification of the results in situ is essential. Nevertheless, the results of this study provide intriguing implications on how to target HRI for the service robot examined.

Although both HRI and Communication Science often trace their origins to the transdisciplinary cybernetics of the 20th century, they have since developed in relative isolation, with scant scholarly exchange concerning the similarities and differences in their assumptions, insights, and approaches. The purpose of this half-day workshop is to explore the ways in which traditional communication theory and Human-Machine Communication theory from the discipline of Communication Science can be applied and be utilized in HRI studies.

We propose a new theoretical framework assuming that embodiment effects in HAI and HRI are mediated by users' perceptions of an artificial entity's body-related capabilities. To enable the application of our framework to foster more theoretical-driven research, we developed a new self-report measurement that assesses bodilyrelated perceptions of the embodiment and corporeality - which we reveal as not being a binary characteristic of artificial entities. For the development and validation of the new scale we conducted two surveys and one video-based experiment. Exploratory factor analysis reveal a four-factorial solution with good reliability (Study 2, n = 442), which was confirmed via confirmatory factor analysis (Study 3, n = 260). In addition, we present first insights into the explanatory power of the scale: We reveal that humans? perceptions of an artificial entity's capabilities vary between virtual and physical embodiments, and that the evaluation of the artificial counterpart can be explained through the perceived capabilities. Practical applications and future research lines are discussed.

This methodological article discusses the influence of individuals’ beliefs about their abilities to use and control robotic technologies on their evaluation of human-robot-interaction (HRI). We conducted three surveys to develop and validate a new measure of Self-Efficacy in HRI. Exploratory factor analysis revealed a two-factorial (factors perceived self-efficacy and loss of control) solution with good reliability (Study 1, n = 201). Confirmatory factor analysis did not confirm the two-factorial structure. Instead, it revealed a better model fit for a one-factorial solution for a German (Study 2, n = 450) and an English version (Study 3, n = 209) of the scale with good indices for convergent and divergent validity. The final questionnaire with 18 items was used in two experimental studies (Study 4, n = 120). We found that interacting with a robot increased self-efficacy and that individual changes in self-efficacy predict more positive evaluations within a student sample, but not a sample of seniors. Interviews with seniors from this study suggested shortening the scale, and revising the instructions and answering scheme. The revised scale was again subject to confirmatory factor analysis (Study 5, n = 198), confirming the one-factorial solution for the German and the English version of the scale. We discuss potential use cases for the scale in HRI research.

The goal of this work is to explore the influence of do-it-yourself customization of a robot on technologically experienced students and unexperienced elderly users' perceived self-efficacy in HRI, uncertainty, and evaluation of the robot and interaction. We introduce the Self-Efficacy in HRI Scale and present two experimental studies. In study 1 (students, n=60) we found that any interaction with the robot increased self-efficacy, regardless of whether this interaction involves customization or not. Moreover, individual increases in self-efficacy predict more positive evaluations. In a second study with elderly users (n=60) we could not replicate the general positive effect of the interaction on self-efficacy. Again, we did not find the hypothesized stronger effect of customization on self-efficacy, nor did we find that relationship between self-efficacy increase and evaluation. We discuss limitations of the setting and for questionnaire design for elderly participants.

First evidence suggests that introducing robots by means of a narrative story can lead to more positive interactions and evaluations [1]. It is unclear whether this positive framing of robots by narratives works equally for different robot design approaches and appearances. To address this open question we conducted 2×6 between-subjects online experiment and varied the introduction (narrative vs. instruction manual) and appearance of the robot (6 different robot appearances). We replicated previous results on evaluation effects for different robot appearances. Results indicate that robots introduced by a narrative story were evaluated as being more likable, intelligent, autonomous, and humanlike. They were also perceived to be less mechanical and less uncanny. However, there were no interaction effects between narration and robot appearance suggesting that narration is beneficial for robots regardless of their appearance and hence is a strong mechanism to shape positive expectations before actually interacting with a robot.

Robots are more and more leaving our labs and entering natural interaction settings, such as homes, care facilities, factories, kindergartens, museums, and many more. In the HRI research community, we are aware of all the challenges involved in studying autonomously behaving agents “in the wild”. In order “not to go wild” we want to discuss best practices as well as pitfalls in studying robots in natural interaction settings. Specifically, we want to focus on challenges in the development of systems for everyday usage in peoples' homes and on challenges in evaluating these systems in the wild, especially with regard to long-term interaction. We want to discuss and explore common and new methodological approaches to study HRI outside the lab, and collect recommendations for fellow researchers. In tandem, we want to reflect our visions for the “new era of socially capable robots” and how we as robot developers and researchers imagine them to integrate into the fabrics of our everyday life.

In this paper we present a system for all and sundry to create robotic applications which is characterized by adaptivity on different levels. First, users are enabled to create their own applications (e.g. play a card game with robot) by the usage of a decision making framework for robot companions. Second, within a created application the robot itself adapts its behavior via user feedback based on a decision making algorithm (e.g. teach the robot a card game based on user feedback). In dependency of the user's expertise, he or she has different possibilities of enhancing the robot's capabilities. Especially for the non-expert user a tool has been developed which provides a graphical user interface to configure applications. The usability of the tool has been evaluated with 5 participants of the age group 40+. The results show that the technical requirements to include non-experts are fulfilled by the framework but also reveal ways to improve the tool, such as the placement of the assistance mechanisms offered to the user.

Against the background of the uncanny valley hypothesis [1] and its conceptual shortcomings this study aims at identifying design characteristics which determine the evaluation of robots. We conducted a web-based survey with standardized pictures of 40 robots which were evaluated by 151 participants. A cluster analysis revealed six clusters of robots. The results are discussed with regard to implications for the uncanny valley hypothesis.

Presence is usually assessed via a variety of subjective and objective measures. However, constraints often result in subjective measurements using questionnaires as a key method of data collection. In this paper we present a study of 44 participants of a collaborative augmented reality game known as TimeWarp which used both subjective and objective behavioral measures. Behavior as coded from video recordings of one scene of the game and self-reports about feelings of presence were compared. Our findings indicate that pointing behavior and verbal responses to the virtual content are correlated negatively to sense of presence. We further investigated the influence of subjectively perceived interactivity on perceived presence. We found that the interaction possibilities perceived by the participants predicted their experience of social presence with the virtual characters in the game. Furthermore, playing together with another person did not result in decreased social presence of the virtual characters. Implications for presence research are discussed.

Since most robots are not easily displayable in real-life scenarios, only a few studies investigate users' behavior towards humanoids or androids in a natural environment. We present an observational field study and data on unscripted interactions between humans and the android robot "Geminoid HI-1". First results show that almost half of the subjects mistook Geminoid HI-1 for a human. Even those who recognized the android as a robot rather showed interest than negative emotions and explored the robots capabilities.

The EU project SERA (Social Engagement with Robots and Agents) provided the unique opportunity to collect real field data of people interacting with a robot companion in their homes. In the course of three iterations, altogether six elderly participants took part. Following a multi-methodological approach, the continuous quantitative and qualitative description of user behavior on a very fine-grained level gave us insights into when and how people interacted with the robot companion. Post-trial semi-structured interviews explored how the users perceived the companion and revealed their attitudes. Based on this large data set, conclusions can be drawn on whether people show signs of bonding and how their relation to the robot develops over time. Results indicate large inter-individual differences with regard to interaction behavior and attitudes. Implications for research on companions are discussed.