In-vehicle sensing technology has gained tremendous attention due to its ability to support major technological developments, such as connected vehicles and self-driving cars. In-vehicle sensing data are invaluable and important data sources for traffic management systems. In this paper we propose an innovative architecture of unobtrusive in-vehicle sensors and present methods and tools that are used to measure the behavior of drivers. The proposed architecture including methods and tools are used in our NIH project to monitor and identify older drivers with early dementia

翻译：车内感知技术因其支持车联网和自动驾驶汽车等重大技术发展的能力而受到极大关注。车内感知数据是交通管理系统宝贵且重要的数据源。本文提出了一种创新的非侵入式车载传感器架构，并介绍了用于测量驾驶员行为的方法与工具。该架构及其所包含的方法与工具已应用于我们的美国国立卫生研究院项目，用于监测和识别患有早期痴呆的老年驾驶员。