A Machine Vision Approach for Estimating Motion Discomfort in Simulators and in Self-Driving Vehicles
| 项目名称： | A Machine Vision Approach for Estimating Motion Discomfort in Simulators and in Self-Driving Vehicles |
| 摘要： | Motion discomfort represents a persistent problem in driving simulators and is expected to be as problematic in highly automated vehicles. This problem can compromise data collection and research validity in simulators, and very likely discourage people from riding in automated vehicles; undermining their potential safety benefits. Monitoring motion sickness can help mitigate its negative effects. However, most of the existing research focuses on physiological research and subjective reporting to quantify motion sickness, which is impractical and does not allow for online monitoring; respectively. Some studies have linked motion sickness to increased yawning. Yet, there is no system to monitor motion sickness in real-time. This project will develop a machine vision algorithm that monitors facial features of drivers and detect any signs of motion discomfort in real-time. The research team will use data collected from 36 drivers who participated in an automated simulator driving study that is expected to induce motion sickness. |
| 状态： | Completed |
| 资金： | 75000 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 管理组织： | University of Iowa, Iowa City |
| 执行机构： | University of Wisconsin-Madison |
| 主要研究人员： | Lee, John D |
| 开始时间： | 20180501 |
| 预计完成日期： | 20191231 |
| 实际结束时间： | 0 |
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