Automated biomechanical testing has great potential for the development of VR applications, as initial insights into user behaviour can be gained in silico early in the design process. In particular, it allows prediction of user movements and ergonomic variables, such as fatigue, prior to conducting user studies. However, there is a fundamental disconnect between simulators hosting state-of-the-art biomechanical user models and simulators used to develop and run VR applications. Existing user simulators often struggle to capture the intricacies of real-world VR applications, reducing ecological validity of user predictions. In this paper, we introduce SIM2VR, a system that aligns user simulation with a given VR application by establishing a continuous closed loop between the two processes. This, for the first time, enables training simulated users directly in the same VR application that real users interact with. We demonstrate that SIM2VR can predict differences in user performance, ergonomics and strategies in a fast-paced, dynamic arcade game. In order to expand the scope of automated biomechanical testing beyond simple visuomotor tasks, advances in cognitive models and reward function design will be needed.

翻译：自动化生物力学测试在虚拟现实（VR）应用开发中具有巨大潜力，因为设计过程早期即可通过计算机模拟初步获取用户行为洞察。具体而言，它能在开展用户研究前预测用户动作及人机工效学变量（如疲劳度）。然而，承载先进生物力学用户模型的模拟器与用于开发运行VR应用的模拟器之间存在根本性脱节。现有用户模拟器往往难以捕捉真实VR应用的复杂性，降低了用户预测的生态效度。本文提出SIM2VR系统，通过建立两个进程间的持续闭环，使用户模拟与特定VR应用保持同步。这首次实现了在真实用户交互的同一VR应用中直接训练模拟用户。我们通过快节奏动态街机游戏证明，SIM2VR能够预测用户表现、人机工效及行为策略的差异。为将自动化生物力学测试范围拓展至简单视觉运动任务之外，未来需在认知模型与奖励函数设计方面取得进展。