Exploring the Role of Expected Collision Feedback in Crowded Virtual Environments

TL;DR

This study investigates how the expectancy of collision feedback influences user perception and navigation in crowded virtual environments. By manipulating auditory cues, vibrotactile feedback, and a collision-belief adaptation (COLBLF), across corridor and street-crossing tasks, the authors show that expected collision feedback modulates global navigation and presence, with audio enhancing copresence and vibrotactile feedback shaping local avoidance. The adaptation phase to induce belief in real collisions amplifies presence, while actual collisions remain infrequent; the results provide actionable guidance for designing VR crowd experiences and collision-feedback strategies. The work highlights the importance of matching user expectations to enhance realism and engagement in virtual crowds, while acknowledging limitations such as sample size and task scope, and pointing toward broader investigations of longer tasks and varied scenarios.

Abstract

An increasing number of virtual reality applications require environments that emulate real-world conditions. These environments often involve dynamic virtual humans showing realistic behaviors. Understanding user perception and navigation among these virtual agents is key for designing realistic and effective environments featuring groups of virtual humans. While collision risk significantly influences human locomotion in the real world, this risk is largely absent in virtual settings. This paper studies the impact of the expected collision feedback on user perception and interaction with virtual crowds. We examine the effectiveness of commonly used collision feedback techniques (auditory cues and tactile vibrations) as well as inducing participants to expect that a physical bump with a real person might occur, as if some virtual humans actually correspond to real persons embodied into them and sharing the same physical space. Our results indicate that the expected collision feedback significantly influences both participant behavior (encompassing global navigation and local movements) and subjective perceptions of presence and copresence. Specifically, the introduction of a perceived risk of actual collision was found to significantly impact global navigation strategies and increase the sense of presence. Auditory cues had a similar effect on global navigation and additionally enhanced the sense of copresence. In contrast, vibrotactile feedback was primarily effective in influencing local movements.

Figures (6)

• Figure 2: Corridor scenario showing the direct path with a continuous line and the detour path with a dotted line (top). Crossing scenario (bottom).
• Figure 3: Visual illustration of Clearance and Torso measures. (a) The distances between the user avatar's root position and every agent's root position are calculated at timestamp $i$ (projected onto the ground); $d_i$ is the shortest distance at this timestamp. (b) Torso refers to the cosine of the angle, $\mathbf{\alpha}$, between the torso forward vector (in light salmon), $\mathbf{\hat{s}}$, and the hips forward vector (in light blue), $\mathbf{\hat{l}}$. The torso and hips forward vectors are computed from the forward vectors of shoulders and upper legs respectively. The Torso value changes when a user rotates the torso to avoid nearby agents.
• Figure 4: Box plots for all objective and subjective measurements, except Path. Each box encloses the middle 50% of the data for each condition. The thick horizontal lines denote the medians. a stands for enabled AUDIO, v for VIBR, c for COLBLF. n means the corresponding factor is disabled.
• Figure 5: Predicted probability of the detour path from binomial generalized linear mixed-effects models of AUDIO, VIBR and COLBLF on Path ($0$ stands for factor disabled, $1$ stands for factor enabled).
• Figure 6: Percentage of time participants walked, in the Corridor scenario, using a detour path (green) and direct path (purple) for each condition.