基于视觉垂直估计的运动病建模及其在自动驾驶个人移动车辆中的应用
Motion Sickness Modeling with Visual Vertical Estimation and Its Application to Autonomous Personal Mobility Vehicles
AI总结：
本文提出了一种结合视觉垂直信息的 6 自由度 SVC-VV 模型，用于预测运动病并应用于自动驾驶个人移动车辆。
摘要：
Level 3-5 自动驾驶个人移动车辆 (APMV) 和汽车的乘客 (驾驶员) 在驾驶过程中可以执行非驾驶任务，如阅读书籍和智能手机。已指出此类活动可能增加运动病的发生。许多研究已开展以构建对策，其中开发了多种计算运动病模型。许多模型基于主观垂直冲突 (SVC) 理论，该理论描述了人体感官器官感知的垂直方向变化与中枢神经系统预期的垂直方向变化之间的差异。此类模型预计可应用于自动驾驶场景。然而，目前没有计算模型能够整合视觉垂直信息与前庭感觉。我们提出了一种 6 自由度 SVC-VV 模型，通过在传统六自由度 SVC 模型中增加一个视觉感知的垂直块，以从图像数据中模拟人类的视觉输入来预测 VV 方向。因此，提出了一种简单的基于图像的 VV 估计方法。作为所提模型的验证，本文聚焦于描述乘客在使用 APMV 时阅读书籍会增加运动病的事实，假设 VV 在其中起重要作用。在静态实验中，证明了所提出方法估计的 VV 准确描述了重力加速度方向，具有低的均方误差。此外，使用 APMV 进行的驾驶实验结果表明，所提出的 6 自由度 SVC-VV 模型能够描述当 VV 和重力加速度方向不同时所经历的运动病增加情况。
英文摘要：
Passengers (drivers) of level 3-5 autonomous personal mobility vehicles (APMV) and cars can perform non-driving tasks, such as reading books and smartphones, while driving. It has been pointed out that such activities may increase motion sickness. Many studies have been conducted to build countermeasures, of which various computational motion sickness models have been developed. Many of these are based on subjective vertical conflict (SVC) theory, which describes vertical changes in direction sensed by human sensory organs vs. those expected by the central nervous system. Such models are expected to be applied to autonomous driving scenarios. However, no current computational model can integrate visual vertical information with vestibular sensations. We proposed a 6 DoF SVC-VV model which add a visually perceived vertical block into a conventional six-degrees-of-freedom SVC model to predict VV directions from image data simulating the visual input of a human. Hence, a simple image-based VV estimation method is proposed. As the validation of the proposed model, this paper focuses on describing the fact that the motion sickness increases as a passenger reads a book while using an AMPV, assuming that visual vertical (VV) plays an important role. In the static experiment, it is demonstrated that the estimated VV by the proposed method accurately described the gravitational acceleration direction with a low mean absolute deviation. In addition, the results of the driving experiment using an APMV demonstrated that the proposed 6 DoF SVC-VV model could describe that the increased motion sickness experienced when the VV and gravitational acceleration directions were different.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
