In virtual reality, creating intelligent virtual characters has been a long-lasting endeavor. However, while researchers have investigated several aspects of a virtual character’s intelligence, little attention has been paid to the impact of the implemented intelligence levels assigned to a virtual character during human–virtual character collaboration. Thus, we conducted a within-group study ( \(N=24\) ) to explore how three different intelligence levels (low vs. medium vs. high) assigned to a virtual character can impact how study participants perceive that virtual character and interact with the task they are instructed to complete. Specifically, for our study, we developed a jigsaw puzzle game and instructed our participants to solve it with the help of a virtual character. During the jigsaw puzzle solving process, we collected application logs related to how the participants executed the task and observed the virtual environment. Moreover, after each condition, we asked the participants to respond using a questionnaire that examined their social presence, how they perceived the character’s intelligence and compared it with their own, and how they rated the virtual character’s realism. Our results indicated that the different intelligence levels assigned to the virtual characters impacted participants’ responses on several variables, including co-presence, perceived intelligence, intelligence comparison, and character interaction and behavior realism. Moreover, based on the collected logged data, we found that the intelligence levels assigned to our virtual character significantly impacted the performance of our participants. Our results could be valuable to the research community for creating more engaging experiences with intelligent virtual characters for collaborative tasks in immersive environments.

We explored how study participants interacted with virtual characters in a virtual reality study. Specifically, we developed a 3 (proximity: close vs. middle vs. far) $\times 2$ (gesture: passive vs. active) experimental design (N = 26) to understand how combinations of proximity between two virtual characters and gestures assigned to them influence study participants’ self-reported ratings (co-presence, attentional allocation, behavioral interdependence, emotional reactivity, and perceived politeness). We also examined their avoidance movements (duration, trajectory length, and speed) and their avoidance decisions (passing through/around and minimum distance side). We collected both survey responses and our participants’ trajectories. Our study revealed that 1) the proximity factor impacted how our participants rated their co-presence and behavioral interdependence, as well as whether they decided to pass through or around the virtual characters, and 2) the gesture factor impacted how participants rated their behavioral interdependence, emotional reactivity, perceived politeness, and also affected their duration, trajectory length, and speed. Our research contributes to understanding personal space and social norms in virtual environments, offering valuable insights for virtual reality developers on the importance of social dynamics in designing interactions with virtual characters.

Virtual character’s intelligence and task complexity are essential components for the design of collaboration between humans and virtual characters. However, studies have yet to explore the impact of a virtual character’s intelligence and task complexity during a collaboration task. To explore these impacts, we implemented a jigsaw puzzle co-solving experience and conducted a within-group study (N = 27) following a 2 (intelligence: low vs. high) × 2 (complexity: low vs. high) study design. During the puzzle co-solving process, we collected participants’ gaze data for each experimental condition. After our participants completed each condition (co-solved the jigsaw puzzle), they answered a survey that captured several variables. We found several significant main and interaction effect results indicating the impact of the virtual character’s intelligence and the task’s complexity. Specifically, the virtual character’s intelligence impacted most survey ratings, including the virtual character’s intelligence, perceived collaboration, self-confidence, and perceived contribution. Also, the task complexity affected perceived collaboration, the virtual character’s public awareness, and self-confidence. Furthermore, we found that the virtual character’s intelligence and complexity dominantly impacted our participants’ task load and perception of the virtual character’s confidence. Moreover, we found that our participants gazed at the virtual character and the puzzle piece more often than the puzzle goal across all experimental conditions. Our findings can inform the design of intelligent virtual characters that co-solve tasks with users.

Although researchers have explored how humans perceive the intelligence of virtual characters, few studies have focused on the ability of intelligent virtual characters to fix their mistakes. Thus, we explored the self-correction behavior of a virtual character with different intelligence capabilities in a within-group design ( \(N=23\) ) study. For this study, we developed a virtual character that can solve a jigsaw puzzle whose self-correction behavior is controlled by two parameters, namely, Intelligence and Accuracy of Self-correction . Then, we integrated the virtual character into our virtual reality experience and asked participants to co-solve a jigsaw puzzle. During the study, our participants were exposed to five experimental conditions resulting from combinations of the Intelligence and Accuracy of Self-correction parameters. In each condition, we asked our participants to respond to a survey examining their perceptions of the virtual character’s intelligence and awareness (private, public, and surroundings awareness) and user experiences, including trust, enjoyment, performance, frustration, and desire for future interaction. We also collected application logs, including participants’ dwell gaze data, completion times, and the number of puzzle pieces they placed to co-solve the jigsaw puzzle. The results of all the survey ratings and the completion time were statistically significant. Our results indicated that higher levels of Intelligence and Accuracy of Self-correction enhanced not only our participants’ perceptions of the virtual character’s intelligence, awareness (private, public, and surroundings), trustworthiness, and performance but also increased their enjoyment and desire for future interaction with the virtual character while reducing their frustration and completion time. Moreover, we found that as the Intelligence and Accuracy of Self-correction increased, participants had to place fewer puzzle pieces and needed less time to complete the jigsaw puzzle. Finally, regardless of the experimental condition to which we exposed our participants, they gazed at the virtual character for more time compared to the puzzle pieces and puzzle goal in the virtual environment.

We explored the avoidance movement behaviors of study participants immersed in a virtual reality environment. We placed a static virtual character at the midpoint between the start and target spot for the avoidance task, and a virtual walker character in front of the starting spot and scripted it to reach the target spot. Participants were placed behind the virtual walker in order to measure its influence on participants’ behavior. We developed nine experimental conditions assigned to the virtual walker character by following a 3 (speed: slow vs. normal vs. fast walking speed) $\times 3$ (proximity: close vs. middle vs. far proximity to the static virtual character) study design. For this within-group study, we collected data from 22 study participants to explore how speed and proximity walking patterns assigned to a virtual walker character could impact participants’ avoidance movement behaviors and decisions. Our data revealed that 1) the speed factor impacted the participants’ avoidance movement behavior; 2) the proximity factor did not significantly impact the participants’ avoidance movement behavior; 3) the virtual walker character did not significantly impact participants’ avoidance decisions regarding the static virtual character; 4) in all examined conditions, the side-by-side distances between the participants and the static virtual character were inside the social space according to the proxemics model; and 5) in conditions in which a slow virtual walker character was present or in the condition of normal speed and far proximity, we observed an increased number of participants pass the virtual walker character.

This virtual reality study was conducted to assess the impact of the appearance of virtual characters on the avoidance movement behavior of participants. Five experimental conditions were examined. Under each condition, one of the five different virtual characters (classified as mannequin, human, cartoon, robot, and zombie) was studied. Each participant had to experience only one condition and was asked to perform the collision avoidance tasks two times. During the walking task, the motion of participants was recorded. After finishing the collision avoidance segment of the study, a questionnaire that examined different concepts (emotional reactivity, emotional contagion, attentional allocation, behavioral independence, perceived skill, presence, immersion, virtual character realism, and virtual character unpleasantness) was distributed to the participants. Based on the collected measurements (avoidance movement behavior and self-reported ratings), we tried to understand the effects of the appearance of a virtual character on the avoidance movement behavior, and its possible correlation to subjective ratings. The results obtained from this study indicated that the appearance of the virtual characters did affect the avoidance movement behavior and also some of the examined concepts. Additionally, participant avoidance movement behavior correlates with some subjective ratings.

This paper examines a common problem found in a number of virtual reality setups—mismatches between real and virtual environments. Specifically, this paper investigates whether the mismatching between a real and a virtual environment in terms of appearance and physical constraints can affect the arousal (electrodermal activity) and movement behavior in the participants. For this study, one baseline condition and four mismatch conditions that examine different mismatching types were developed and tested in a between-group study design. The participants were immersed in a virtual environment and were asked to walk in a direction given to them along a provided path. During that time, electrodermal activity and the walking motion of participants were captured to assess potential alterations in their arousal and movement behavior respectively. Results obtained from this study indicate significant differences in the electrodermal activity and movement behavior of participants, especially when walking in a virtual environment that is mismatched both in appearance and physical constraints. Even though to a lesser degree, evidence was also found that correlates electrodermal activity with movement behavior. Limitations and future research directions are discussed.

Abstract The aim of our study was to investigate whether different tactile feedback conditions could affect the behavior of participants who were instructed to walk within a virtual reality environment surrounded by a virtual crowd of people. A road crossing scenario that takes place in a virtual metropolitan city was developed for this study. Participants were asked to walk toward the opposite sidewalk while wearing a tactile vest. At each road crossing, one of several tactile feedback conditions was generated, including No Tactile, Side Tactile, Back Tactile, Front Tactile, Accurate Tactile, and Random Tactile. During the virtual road crossing, the movement of the participants was captured, and movement‐related measurements were extracted and analyzed to evaluate the effects of tactile feedback on the participant's movement behavior. Additional data were collected through the distribution of a questionnaire to consider self‐reported ratings of the experimental conditions. The results revealed that tactile feedback conditions had significant effects on movement behavior, while the participants' ratings also indicated that they were affected by the tactile feedback conditions. We found that when the participants were immersed in a high‐density crowd simulation, they became sensitive to tactile feedback. However, they were not able to distinguish between the accurate feedback and the random feedback.

Abstract We investigated the movement behavior of participants walking within a virtual crowd in an immersive virtual environment. We investigated three different parameters that characterize a moving virtual crowd: density, speed, and direction. An immersive road‐crossing scenario that took place in a virtual metropolitan city was created. In this scenario, the participants were instructed to walk toward the opposite sidewalk. Three measurements (speed, deviation, and trajectory length) were used to evaluate the impact of the parameters assigned to the virtual crowd on the movement behavior of the participants. Significant results were found for both the main and interaction effects. The results suggested that the high density, low speed, and diagonal direction situations associated with the virtual crowd had the greatest impacts on the speed, deviation, and trajectory lengths of participants when they walked in a virtual environment and were surrounded by a moving virtual population.

A virtual reality study was conducted to understand participants' anxiety when immersed in a virtual reality trip with a self-driving car. Participants were placed as passengers in a virtual car, and they were seated in the co-driver seat. Five different conditions were developed and examined. For this experiment, the Anxiety Modality Questionnaire that captures the cognitive anxiety of participants was used. The obtained results indicated that the participants' level of anxiety for the partial awareness of the driver condition is influenced less than expected. Specifically, lower levels of anxiety were found when the driver is either fully or partially aware of the traffic and the behavior of the car, and higher anxiety levels were found when the driver is completely unaware.

The present study investigates users' movement behavior in a virtual environment when they attempted to avoid a virtual character. At each iteration of the experiment, four conditions (Self-Avatar LookAt, No Self-Avatar LookAt, Self-Avatar No LookAt, and No Self-Avatar No LookAt) were applied to examine users' movement behavior based on kinematic measures. During the experiment, 52 participants were asked to walk from a starting position to a target position. A virtual character was placed at the midpoint. Participants were asked to wear a head-mounted display throughout the task, and their locomotion was captured using a motion capture suit. We analyzed the captured trajectories of the participants' routes on four kinematic measures to explore whether the four experimental conditions influenced the paths they took. The results indicated that the Self-Avatar LookAt condition affected the path the participants chose more significantly than the other three conditions in terms of length, duration, and deviation, but not in terms of speed. Overall, the length and duration of the task, as well as the deviation of the trajectory from the straight line, were greater when a self-avatar represented participants. An additional effect on kinematic measures was found in the LookAt (Gaze) conditions. Implications for future research are discussed.