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Modeling the interactions between users and social groups of virtual agents (VAs) is vital in many virtual-reality-based applications. However, only little research on group encounters has been conducted yet. We intend to close this gap by focusing on the distinction between joining and passing-by a group. To enhance the interactive capacity of VAs in these situations, knowing the user’s objective is required to showreasonable reactions. To this end,we propose a classification scheme which infers the user’s intent based on social cues such as proxemics, gazing and orientation, followed by triggering believable, non-verbal actions on the VAs.We tested our approach in a pilot study with overall promising results and discuss possible improvements for further studies.

Generating natural embodied conversational agents within virtual spaces crucially depends on speech sounds and their directionality. In this work, we simulated directional filters to not only add directionality, but also directionally adapt each phoneme. We therefore mimic reality where changing mouth shapes have an influence on the directional propagation of sound. We conducted a study (n = 32) evaluating naturalism ratings, preference and distinguishability of omnidirectional speech auralization compared to static and dynamic, phoneme-dependent directivities. The results indicated that participants cannot distinguish dynamic from static directivity. Furthermore, participants’ preference ratings aligned with their naturalism ratings. There was no unanimity, however, with regards to which auralization is the most natural.

Virtual-reality-based interactions with virtual agents (VAs) are likely subject to similar influences as human-human interactions. In either real or virtual social interactions, interactants try to maintain their personal space (PS), an ubiquitous, situative, flexible safety zone. Building upon larger PS preferences to humans and VAs with angry facial expressions, we extend the investigations to whole-body emotional expressions. In two immersive settings–HMD and CAVE–66 males were approached by an either happy, angry, or neutral male VA. Subjects preferred a larger PS to the angry VA when being able to stop him at their convenience (Sample task), replicating previous findings, and when being able to actively avoid him (PassBy task). In the latter task, we also observed larger distances in the CAVE than in the HMD.

the flow of virtual crowds in a direct and interactive manner. Here, options to redirect a flow by sketching barriers, or guiding entities based on a sketched network of connected sections are provided. As virtual crowds are increasingly often embedded into virtual reality (VR) applications, 3D authoring is of interest.

In this preliminary work, we thus present a sketch-based approach for VR. First promising results of a proof-of-concept are summarized and improvement suggestions, extensions, and future steps are discussed.

Simulating a realistic navigation of virtual pedestrians through virtual environments is a recurring subject of investigations. The various mathematical approaches used to compute the pedestrians’ paths result, i.a., in different computation-times and varying path characteristics. Customizable parameters, e.g., maximal walking speed or minimal interpersonal distance, add another level of complexity. Thus, choosing the best-fitting approach for a given environment and use-case is non-trivial, especially for novice users.

To facilitate the informed choice of a specific algorithm with a certain parameter set, crowd simulation frameworks such as Menge provide an extendable collection of approaches with a unified interface for usage. However, they often miss an elaborated visualization with high informative value accompanied by visual analysis methods to explore the complete simulation data in more detail – which is yet required for an informed choice. Benchmarking suites such as SteerBench are a helpful approach as they objectively analyze crowd simulations, however they are too tailored to specific behavior details. To this end, we propose a preliminary design of an advanced graphical user interface providing a 2D and 3D visualization of the crowd simulation data as well as features for time navigation and an overall data exploration.

Embodied conversational agents become more and more important in various virtual reality applications, e.g., as peers, trainers or therapists. Besides their appearance and behavior, appropriate speech is required for them to be perceived as human-like and realistic. Additionally to the used voice signal, also its auralization in the immersive virtual environment has to be believable. Therefore, we investigated the effect of adding directivity to the speech sound source. Directivity simulates the orientation dependent auralization with regard to the agent's head orientation. We performed a one-factorial user study with two levels (n=35) to investigate the effect directivity has on the perceived social presence and realism of the agent's voice. Our results do not indicate any significant effects regarding directivity on both variables covered. We account this partly to an overall too low realism of the virtual agent, a not overly social utilized scenario and generally high variance of the examined measures. These results are critically discussed and potential further research questions and study designs are identified.

When designing the behavior of embodied, computer-controlled, human-like virtual agents (VA) serving as temporarily required assistants in virtual reality applications, two linked factors have to be considered: the time the VA is visible in the scene, defined as presence time (PT), and the time till the VA is actually available for support on a user’s calling, defined as approaching time (AT).

Complementing a previous research on behaviors with a low VA’s PT, we present the results of a controlled within-subjects study investigating behaviors by which the VA is always visible, i.e., behaviors with a high PT. The two behaviors affecting the AT tested are: following, a design in which the VA is omnipresent and constantly follows the users, and busy, a design in which theVAis self-reliantly spending time nearby the users and approaches them only if explicitly asked for. The results indicate that subjects prefer the following VA, a behavior which also leads to slightly lower execution times compared to busy.

Personal space (PS), the flexible protective zone maintained around oneself, is a key element of everyday social interactions. It, e.g., affects people's interpersonal distance and is thus largely involved when navigating through social environments. However, the PS is regulated dynamically, its size depends on numerous social and personal characteristics and its violation evokes different levels of discomfort and physiological arousal. Thus, gaining more insight into this phenomenon is important.

We contribute to the PS investigations by presenting the results of a controlled experiment in a CAVE, focusing on German males in the age of 18 to 30 years. The PS preferences of 27 participants have been sampled while they were approached by either a single embodied, computer-controlled virtual agent (VA) or by a group of three VAs. In order to investigate the influence of a VA's emotions, we altered their facial expression between angry and happy. Our results indicate that the emotion as well as the number of VAs approaching influence the PS: larger distances are chosen to angry VAs compared to happy ones; single VAs are allowed closer compared to the group. Thus, our study is a foundation for social and behavioral studies investigating PS preferences.

When interacting and communicating with virtual agents in immersive environments, the agents’ behavior should be believable and authentic. Thereby, one important aspect is a convincing auralizations of their speech. In this work-in progress paper a study design to evaluate the effect of adding directivity to speech sound source on the perceived social presence of a virtual agent is presented. Therefore, we describe the study design and discuss first results of a prestudy as well as consequential improvements of the design.

The concept of personal space is a key element of social interactions. As such, it is a recurring subject of investigations in the context of research on proxemics. Using virtual-reality-based experiments, we contribute to this area by evaluating the direct effects of emotional expressions of an approaching virtual agent on an individual’s behavioral and physiological responses. As a pilot study focusing on the emotion expressed solely by facial expressions gave promising results, we now present a study design to gain more insight.

Personal Space (PS) is regulated dynamically by choosing an appropriate interpersonal distance when navigating through social environments. This key element in social interactions is influenced by numerous social and personal characteristics, e.g., the nature of the relationship between the interaction partners and the other’s sex and age. Moreover, affective contexts and expressions of interaction partners influence PS preferences, evident, e.g., in larger distances to others in threatening situations or when confronted with angry-looking individuals. Given the prominent role of emotional expressions in our everyday social interactions, we investigate how emotions affect PS adaptions.

Controlling user-agent-interactions by means of an external operator includes selecting the virtual interaction partners fast and faultlessly. However, especially in immersive scenes with a large number of potential partners, this task is non-trivial.

Thus, we present a score-based recommendation system supporting an operator in the selection task. Agents are recommended as potential partners based on two parameters: the user’s distance to the agents and the user’s gazing direction. An additional graphical user interface (GUI) provides elements for configuring the system and for applying actions to those agents which the operator has confirmed as interaction partners.

Traditionally, experimental economics uses controlled and incentivized field and lab experiments to analyze economic behavior. However, investigating peer effects in the classic settings is challenging due to the reflection problem: Who is influencing whom?

To overcome this, we enlarge the methodological toolbox of these experiments by means of Virtual Reality. After introducing and validating a real-effort sorting task, we embed a virtual agent as peer of a human subject, who independently performs an identical sorting task. We conducted two experiments investigating (a) the subject’s productivity adjustment due to peer effects and (b) the incentive effects on competition. Our results indicate a great potential for Virtual-Reality-based economic experiments.

Computer-controlled, human-like virtual agents (VAs), are often embedded into immersive virtual environments (IVEs) in order to enliven a scene or to assist users. Certain constraints need to be fulfilled, e.g., a collision avoidance strategy allowing users to maintain their personal space. Violating this flexible protective zone causes discomfort in real-world situations and in IVEs. However, no studies on collision avoidance for small-scale IVEs have been conducted yet.

Our goal is to close this gap by presenting the results of a controlled user study in a CAVE. 27 participants were immersed in a small-scale office with the task of reaching the office door. Their way was blocked either by a male or female VA, representing their co-worker. The VA showed different behavioral patterns regarding gaze and locomotion. Our results indicate that participants preferred collaborative collision avoidance: they expect the VA to step aside in order to get more space to pass while being willing to adapt their own walking paths.

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