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Perception and action in virtual environments: Human performance in virtual driving simulators.

机译:虚拟环境中的感知和动作:虚拟驾驶模拟器中的人员表现。

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The real issue and challenge in VR today is not the display, but how to reconcile a person's expectations of reality. Virtual environment (VE) systems are becoming commonplace in research settings. In many cases, virtual environments are used to simulate existing real environments. A common example of this is the use of vehicle simulators (e.g., driving, and flight simulators) for training and assessment of performance in the corresponding real vehicles (cars and aircraft, respectively). In training and assessment, the virtual environment has little inherent interest. Rather, the virtual environment is valuable to the extent that performance in it resembles performance in the simulated real-world environment. This differs from virtual environment applications that do not simulate extant, real worlds. Examples include numerous entertainment applications involving interplanetary travel, fantasy worlds, and so on. Three VE studies with a group of commonalities and unique differences are contrasted here in an attempt to address and assess the components which can be held as reliable indicators of RW performance. I will also examine the limitations of interpreting performance data gathered from VE simulations.; Simulation Validation addressed primarily lane position and gap affordances in comparison to a matched RW environment. Forward Looking Blindspots addressed the perception of threat in a VE and A-pillar issues in automotive design. Deer Avoidance also addressed perception of threat and driver response to enhanced warning signage. The primary foci of these experiments were the validation or more precisely the fidelity of the VE participant's performance relative to the real world (RW) which may to some degree be driven by habitual or at least not-quite-conscious expectations. VEs are limited in many aspects. Wrap around (non head mounted) simulators cannot currently produce glare, parallax, changing resolution in response to accommodation, and any number of RW visual effects. They cannot legally be made to induce pain or threat of injury. Why then should performance data still be used to reflect on or compare to RW performance?
机译:当今虚拟现实中真正的问题和挑战不是展示,而是如何调和人们对现实的期望。虚拟环境(VE)系统在研究环境中变得司空见惯。在许多情况下,虚拟环境用于模拟现有的真实环境。一个常见的例子是使用车辆模拟器(例如,驾驶和飞行模拟器)来训练和评估相应的实际车辆(分别是汽车和飞机)中的性能。在培训和评估中,虚拟环境几乎没有内在的兴趣。相反,虚拟环境的价值在于它的性能类似于模拟的真实环境中的性能。这与不模拟现有真实世界的虚拟环境应用程序不同。示例包括涉及星际旅行,幻想世界等的众多娱乐应用程序。这里比较了三个具有一组共性和独特差异的VE研究,以试图解决和评估可作为RW性能可靠指标的组件。我还将研究解释从VE仿真中收集的性能数据的局限性。与匹配的RW环境相比,仿真验证主要解决了车道位置和间隙补给。前瞻性盲点解决了汽车设计中VE和A柱问题中的威胁感。避免鹿还解决了威胁感和驾驶员对增强警告标志的反应。这些实验的主要重点是验证或更准确地说,VE参与者的表现相对于真实世界(RW)的保真度在某种程度上可能是由习惯或至少不是很自觉的期望所驱动。 VE在很多方面都受到限制。环绕式(非头戴式)模拟器当前无法产生眩光,视差,响应于容纳情况而改变分辨率以及任何数量的RW视觉效果。不能合法地使它们引起疼痛或伤害威胁。那么为什么仍要使用绩效数据来反映或比较RW绩效?

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