Department of Computer Science, University of Würzburg, Germany.
IEEE Trans Vis Comput Graph. 2012 Apr;18(4):538-45. doi: 10.1109/TVCG.2012.55.
Walking is the most natural form of locomotion for humans, and real walking interfaces have demonstrated their benefits for several navigation tasks. With recently proposed redirection techniques it becomes possible to overcome space limitations as imposed by tracking sensors or laboratory setups, and, theoretically, it is now possible to walk through arbitrarily large virtual environments. However, walking as sole locomotion technique has drawbacks, in particular, for long distances, such that even in the real world we tend to support walking with passive or active transportation for longer-distance travel. In this article we show that concepts from the field of redirected walking can be applied to movements with transportation devices. We conducted psychophysical experiments to determine perceptual detection thresholds for redirected driving, and set these in relation to results from redirected walking. We show that redirected walking-and-driving approaches can easily be realized in immersive virtual reality laboratories, e. g., with electric wheelchairs, and show that such systems can combine advantages of real walking in confined spaces with benefits of using vehicle-based self-motion for longer-distance travel.
步行是人类最自然的运动方式，真实的步行界面已经证明了它们在多种导航任务中的优势。随着最近提出的重定向技术，人们可以克服跟踪传感器或实验室设置所施加的空间限制，并且，从理论上讲，现在可以在任意大的虚拟环境中行走。然而，步行作为唯一的运动方式有其缺点，特别是对于长距离，即使在现实世界中，我们也倾向于在长距离旅行中使用被动或主动交通工具来辅助步行。在本文中，我们展示了重定向步行领域的概念可以应用于使用交通工具的运动。我们进行了心理物理学实验来确定重定向驾驶的感知检测阈值，并将这些阈值与重定向步行的结果进行了比较。我们表明，重定向步行和驾驶方法可以很容易地在沉浸式虚拟现实实验室中实现，例如使用电动轮椅，并且表明此类系统可以将在有限空间中使用真实步行的优势与使用基于车辆的自身运动进行长距离旅行的优势相结合。
