Effects of Task Type and Wall Appearance on Collision Behavior in Virtual Environments

TL;DR

This study examines how task motivation and wall appearance affect player behavior in virtual reality, revealing that wall opacity influences collision avoidance and that engaging experiences promote realistic movement.

Contribution

It provides new insights into how visual and task factors influence collision behavior in VR, highlighting the importance of wall opacity and experience engagement.

Findings

Opaque walls effectively deter wall-cutting behavior.

Realistic and diverse experiences promote natural movement.

Wall realism has minimal impact on collision behavior.

Abstract

Driven by the games community, virtual reality setups have lately evolved into affordable and consumer-ready mobile headsets. However, despite these promising improvements, it remains challenging to convey immersive and engaging VR games as players are usually limited to experience the virtual world by vision and hearing only. One prominent example of such open challenges is the disparity between the real surroundings and the virtual environment. As virtual obstacles usually do not have a physical counterpart, players might walk through walls enclosing the level. Thus, past research mainly focussed on multisensory collision feedback to deter players from ignoring obstacles. However, the underlying causative reasons for such unwanted behavior have mostly remained unclear. Our work investigates how task types and wall appearances influence the players' incentives to walk through virtual walls. Therefore, we conducted a user study, confronting the participants with different task motivations and walls of varying opacity and realism. Our evaluation reveals that players generally adhere to realistic behavior, as long as the experience feels interesting and diverse. Furthermore, we found that opaque walls excel in deterring subjects from cutting short, whereas different degrees of realism had no significant influence on walking trajectories. Finally, we use collected player feedback to discuss individual reasons for the observed behavior.