Analyzing Cognitive Demands and Detection Thresholds for Redirected Walking in Immersive Forest and Urban Environments

Redirected walking is a locomotion technique that allows users to naturally walk through large immersive virtual environments (IVEs) by guiding them on paths that might vary from the paths they walk in the real world. While this technique enables the exploration of larger spaces in the IVE via natural walking, previous work has shown that it induces extra cognitive load for the users. On the other hand, previous research has shown that exposure to virtual nature environments can restore users’ diminished attentional capacities and lead to enhanced cognitive performances. Therefore, the aim of this paper is to investigate if the environment in which the user is redirected has the potential to reduce its cognitive demands. For this purpose, we conducted an experiment with 28 participants, who performed a spatial working memory task (i.e., 2-back test) while walking and being redirected with different gains in two different IVEs (i.e., (i) forest and (ii) urban). The results of frequentist and Bayesian analysis are consistent and provide evidence against an effect of the type of IVE on detection thresholds as well as cognitive and locomotion performances. Therefore, redirected walking is robust to the variation of the IVEs tested in this experiment. The results partly challenge previous research findings and, therefore, require future work in this direction.